This document discusses the use of navigation in ORL (ear, nose, and throat) and maxillofacial surgery. It provides an overview of BrainLAB, a company that offers software for surgical planning and navigation. The software allows for more complete resection of diseased tissue, lower reoperation rates, and increased safety and accuracy during surgery. It summarizes the key steps in preoperative planning like defining anatomical planes, segmenting structures, and mirroring templates between sides. Intraoperative navigation registration is described as touchless using a laser surface scan. Advanced features like instrument tracking and image integration are highlighted. BrainLAB is concluded to offer a comprehensive solution for ORL and maxillofacial planning and navigation.
IRJET-Optic Disc and Fovea Localization with GUI in Retinal Fundus ImagesIRJET Journal
This document presents a method for automatically localizing the optic disc and fovea in retinal fundus images using a graphical user interface. The optic disc is localized using 2D convolution and creating a mask by adjusting image brightness. The fovea is detected by taking the mean of the green color channel and applying a Gaussian filter. The algorithm was tested on fundus images and was able to successfully detect the optic disc and fovea, even in images containing exudates. The graphical user interface allows for easy manipulation and visualization of the localization technique.
Possible future avenues for ophthalmic imaging combining advanced techniques and deep learning. "Bubbling under the surface, and inspiration from ‘bioimaging’ in general"
3D localization methods for intracranial electrodesBrian Owens
This document discusses 3D localization methods for intracranial electrodes used in epilepsy surgery planning. It covers the imaging, software tools, and workflow for localizing grid and depth electrodes implanted for invasive monitoring. The document reviews tools like neuronavigation, CURRY, and Brainstorm which allow viewing electrode positions on MRI and coregistering pre-op CT and MRI scans. Accurate localization of electrodes is important for surgical planning and decision making.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Retinal image analysis using morphological process and clustering techniquesipij
This paper proposes a method for the Retinal image analysis through efficient detection of exudates and
recognizes the retina to be normal or abnormal. The contrast image is enhanced by curvelet transform.
Hence, morphology operators are applied to the enhanced image in order to find the retinal image ridges.
A simple thresholding method along with opening and closing operation indicates the remained ridges
belonging to vessels. The clustering method is used for effective detection of exudates of eye. Experimental
result proves that the blood vessels and exudates can be effectively detected by applying this method on the
retinal images. Fundus images of the retina were collected from a reputed eye clinic and 110 images were
trained and tested in order to extract the exudates and blood vessels. In this system we use the Probabilistic
Neural Network (PNN) for training and testing the pre-processed images. The results showed the retina is
normal or abnormal thereby analyzing the retinal image efficiently. There is 98% accuracy in the detection
of the exudates in the retina .
AN AUTOMATIC SCREENING METHOD TO DETECT OPTIC DISC IN THE RETINAijait
The document describes a new automated method for detecting the optic disc in retinal images. The method uses a line operator designed to capture the circular brightness structure of the optic disc. It evaluates image variation along multiple oriented line segments and locates the disc based on the orientation with maximum variation. The method was tested on a dataset and achieved a 96% success rate in detecting the optic disc.
This document discusses various coding issues related to cardiology procedures and services. It provides guidance on proper coding and billing of procedures such as SPECT imaging, echocardiograms, cardiac stents, EKGs and implantable device monitoring. It also addresses changes in Medicare reimbursement rates for some services. The document emphasizes the importance of thorough documentation to support code selection and stresses adhering to coding rules and guidelines set by payers.
IRJET-Optic Disc and Fovea Localization with GUI in Retinal Fundus ImagesIRJET Journal
This document presents a method for automatically localizing the optic disc and fovea in retinal fundus images using a graphical user interface. The optic disc is localized using 2D convolution and creating a mask by adjusting image brightness. The fovea is detected by taking the mean of the green color channel and applying a Gaussian filter. The algorithm was tested on fundus images and was able to successfully detect the optic disc and fovea, even in images containing exudates. The graphical user interface allows for easy manipulation and visualization of the localization technique.
Possible future avenues for ophthalmic imaging combining advanced techniques and deep learning. "Bubbling under the surface, and inspiration from ‘bioimaging’ in general"
3D localization methods for intracranial electrodesBrian Owens
This document discusses 3D localization methods for intracranial electrodes used in epilepsy surgery planning. It covers the imaging, software tools, and workflow for localizing grid and depth electrodes implanted for invasive monitoring. The document reviews tools like neuronavigation, CURRY, and Brainstorm which allow viewing electrode positions on MRI and coregistering pre-op CT and MRI scans. Accurate localization of electrodes is important for surgical planning and decision making.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Retinal image analysis using morphological process and clustering techniquesipij
This paper proposes a method for the Retinal image analysis through efficient detection of exudates and
recognizes the retina to be normal or abnormal. The contrast image is enhanced by curvelet transform.
Hence, morphology operators are applied to the enhanced image in order to find the retinal image ridges.
A simple thresholding method along with opening and closing operation indicates the remained ridges
belonging to vessels. The clustering method is used for effective detection of exudates of eye. Experimental
result proves that the blood vessels and exudates can be effectively detected by applying this method on the
retinal images. Fundus images of the retina were collected from a reputed eye clinic and 110 images were
trained and tested in order to extract the exudates and blood vessels. In this system we use the Probabilistic
Neural Network (PNN) for training and testing the pre-processed images. The results showed the retina is
normal or abnormal thereby analyzing the retinal image efficiently. There is 98% accuracy in the detection
of the exudates in the retina .
AN AUTOMATIC SCREENING METHOD TO DETECT OPTIC DISC IN THE RETINAijait
The document describes a new automated method for detecting the optic disc in retinal images. The method uses a line operator designed to capture the circular brightness structure of the optic disc. It evaluates image variation along multiple oriented line segments and locates the disc based on the orientation with maximum variation. The method was tested on a dataset and achieved a 96% success rate in detecting the optic disc.
This document discusses various coding issues related to cardiology procedures and services. It provides guidance on proper coding and billing of procedures such as SPECT imaging, echocardiograms, cardiac stents, EKGs and implantable device monitoring. It also addresses changes in Medicare reimbursement rates for some services. The document emphasizes the importance of thorough documentation to support code selection and stresses adhering to coding rules and guidelines set by payers.
This document discusses the digital operating room (DOR) and related technologies. It describes 5 levels of DOR maturity from 2005 to 2025, moving from vendor-specific integration to an intelligent infrastructure. A key goal is optimizing intra-operative processes through standards like DICOM and IHE profiles for surgery. Patient and process modeling aims to integrate multimodal data for personalized, evidence-based care. Standards and integrated models may facilitate knowledge discovery from surgical data, situations and workflows.
Document showing the imaging capabilities of the LLTech's Light-CT scanner.
The Light-CT scanner has amazing imaging capabilities due to its ultra high resolution (1.5 X 1.5 X 1 µm). It offers the capability to do optical slices under the surface of the analyzed sample. The imaging process is fast, easy an safe for both the user and the sample. No staining is required.
Brainlab Cranial Navigation. Efficiently combining decisive aspects of neurosurgery.
Brainlab® Cranial 3.0 provides a new user experience on Kick® and Curve™ navigation platforms. Fully
DICOM-based, cranial navigation and Brainlab Elements* can run parallel with instant synchronization
to update navigated image sets with new fusion results, SmartBrush® objects or trajectories.
This webinar discusses defining a universal viewer that would allow radiologists to view medical images from multiple picture archiving and communication systems (PACS) from a single workstation. Presenters describe trends toward centralizing PACS and moving away from separate department-level systems. Challenges of current multiple PACS implementations include a lack of integration, specialized workstations not co-located with physicians, and user interface inefficiencies. A universal viewer is proposed as a thin client solution that could provide radiologists access to images and tools from various PACS from anywhere through separation of the viewer, storage, and application components. This would help standardize workflows and improve productivity.
iScan80, the high-speed 80kHz OCT that sets the
standard for efficiency - perfect for ECPs seeking an affordable and versatile OCT system. It’s ideal for
practices with limited staff since iScan80 delivers consistent scan acquisition with minimal training and
vocally guides patients through an entire exam in any of 12 languages.
The document summarizes the NewTom GO 2D/3D CEPH imaging system. It is an integrated 2D and 3D cephalometric imaging device that provides high resolution images with low radiation exposure. It features advanced imaging capabilities including panoramic, cephalometric, and CBCT imaging as well as connectivity to integration with practice management systems and third party software.
Medical Herb Identification and It’s BenefitsIRJET Journal
This document discusses medical herb identification and its benefits. It presents the methodology used for a project that aims to accurately identify a wide range of medicinal herbs using convolutional neural networks. The document provides background on medicinal herbs and their importance. It then describes the proposed workflow, which involves users registering and uploading images that are pre-processed and run through a CNN model for feature extraction and herb identification. Finally, the document reviews related work and concludes that understanding medical herb identification empowers people to take control of their health.
Who ever said advanced OCT scanning had to be complicated? When an OCT design puts user experience first, it can be simple to learn and easy to use. So it is with the Optovue iSeries. To be any easier they would have to run themselves—and sometimes they do!
But don’t confuse simplicity with performance. The iSeries systems are fully featured and deliver many exclusive Optovue capabilities such as ganglion cell complex (GCC) analysis with focal loss volume (FLV%) and global loss volume (GLV%) metrics, the iWellnessExam® and the Cornea Advance module, which includes Vault Mapping for specialty lens fitting. The iSeries also benefits from a large, ethnically diverse normative database.
Automatic Brain Tumor Segmentation on Multi-Modal MRI with Deep Neural NetworksAndrew Tsuei
This document describes a deep learning approach for automatic brain tumor segmentation on MRI scans. A convolutional neural network is trained on over 3 million patches from 220 glioma patients to classify voxels into tumor subclasses like enhancing tumor, necrosis, and edema. The trained model segments a new MRI scan with over 90% accuracy in under 20 minutes, significantly faster than manual segmentation by experts. This efficient and accurate segmentation technique could maximize treatment effectiveness while maintaining patient privacy in the cloud-based system.
IRJET- A Vision based Hand Gesture Recognition System using Convolutional...IRJET Journal
This document describes a vision-based hand gesture recognition system using convolutional neural networks. The system captures images of hand gestures using a camera, pre-processes the images, and classifies the gestures using a CNN model. The CNN architecture includes convolutional layers, max pooling layers, dropout layers, and fully connected layers. The system was trained on a dataset of images representing 7 different hand gestures. Testing achieved over 90% accuracy in recognizing the gestures. This vision-based approach allows for natural human-computer interaction without physical devices.
This document provides information about an upcoming workshop on sparse theory, applications, and signal processing. The workshop will cover topics including linear algebra, signal transforms, optimization algorithms, sparse representation theory, compressive sensing, and applications in areas like image processing, speech recognition, and medical imaging. Attendees will learn about open problems in the field, standard databases, performance metrics, and will receive training in MATLAB and LaTeX. The workshop aims to provide a forum for researchers and professionals to exchange ideas and advance knowledge in sparse representations and compressive sensing.
This document presents Jeevn-Net, a new neural network architecture for brain tumor segmentation and overall survival prediction. Jeevn-Net uses a cascaded U-Net structure with two U-Nets and applies auto-encoder regularization. It takes in MRI scans and outputs a segmented tumor image with extracted features. Random forest regression is then used to predict survival based on these features. The network achieves state-of-the-art performance for brain tumor segmentation and survival prediction.
The Eyestar 900 features swept-source technology, enabling precise measurement, as well as topographic assessment of the front and back corneal surface and the anterior chamber, including the lens, as well as imaging of all these structures. It also includes cornea-to-retina biometry of the entire eye.
This magazine issue of MAGNETOM Flash focuses on diffusion-weighted imaging applications. It includes articles on using DWI for prostate imaging at 3T, obtaining IVIM f-maps of pancreatic lesions, and monitoring therapy response for nonsecretory multiple myeloma. The issue also features new software version syngo MR B17 and its applications in oncology imaging such as syngo TimCT.
FPGA Implementation of Glaucoma Detection using Neural NetworksIRJET Journal
This document describes a study that implemented glaucoma detection using neural networks on an FPGA. The key steps were:
1. Features were extracted from retinal images including optic disk area, cup area, and neuro-retinal rim area. These features were used as inputs to the neural network.
2. A feedforward backpropagation neural network was trained to classify images as glaucoma or healthy based on the extracted features.
3. The neural network was implemented on a Spartan 3A FPGA to take advantage of its reconfigurability and parallel processing capabilities for neural networks.
4. Testing on sample images from a fundus image database achieved accurate classification of glaucoma and healthy
IRJET- Diversified Segmentation and Classification Techniques on Brain Tu...IRJET Journal
This document summarizes 20 research papers on techniques for detecting brain tumors using medical images like MRI scans. It discusses several techniques for image segmentation, feature extraction, and classification that have been used to automatically detect and diagnose brain tumors. The goal of the work is to consolidate these different techniques and provide new insights on recent approaches to brain tumor image processing. Key methods discussed include convolutional neural networks, random forest classifiers, discrete wavelet transforms, and probabilistic neural networks.
Digital image self-adaptive acquisition in medical x-ray imagingJie Bao
The document describes a method for digital self-adaptive image acquisition in medical x-ray imaging. It discusses x-ray fluoroscopy systems and the challenges of digital acquisition. The method uses digital subtraction to remove background signals, recognizes the valid imaging region, and analyzes the region's histogram to automatically set acquisition parameters like black level, white level, gain and offset for optimal image quality. An experiment validated that this approach improves image quality over traditional methods.
This document summarizes a technology roadmapping course on roadmapping concepts and applications. It includes sections on technology foresight, scenarios, trends and drivers, products and services, supporting systems, examples of technology roadmaps from various industries, and practical issues in roadmap design. The document also presents two case studies, one on a company's use of roadmapping for various business units and technologies, and another on Korea's national technology roadmapping process.
This document discusses the digital operating room (DOR) and related technologies. It describes 5 levels of DOR maturity from 2005 to 2025, moving from vendor-specific integration to an intelligent infrastructure. A key goal is optimizing intra-operative processes through standards like DICOM and IHE profiles for surgery. Patient and process modeling aims to integrate multimodal data for personalized, evidence-based care. Standards and integrated models may facilitate knowledge discovery from surgical data, situations and workflows.
Document showing the imaging capabilities of the LLTech's Light-CT scanner.
The Light-CT scanner has amazing imaging capabilities due to its ultra high resolution (1.5 X 1.5 X 1 µm). It offers the capability to do optical slices under the surface of the analyzed sample. The imaging process is fast, easy an safe for both the user and the sample. No staining is required.
Brainlab Cranial Navigation. Efficiently combining decisive aspects of neurosurgery.
Brainlab® Cranial 3.0 provides a new user experience on Kick® and Curve™ navigation platforms. Fully
DICOM-based, cranial navigation and Brainlab Elements* can run parallel with instant synchronization
to update navigated image sets with new fusion results, SmartBrush® objects or trajectories.
This webinar discusses defining a universal viewer that would allow radiologists to view medical images from multiple picture archiving and communication systems (PACS) from a single workstation. Presenters describe trends toward centralizing PACS and moving away from separate department-level systems. Challenges of current multiple PACS implementations include a lack of integration, specialized workstations not co-located with physicians, and user interface inefficiencies. A universal viewer is proposed as a thin client solution that could provide radiologists access to images and tools from various PACS from anywhere through separation of the viewer, storage, and application components. This would help standardize workflows and improve productivity.
iScan80, the high-speed 80kHz OCT that sets the
standard for efficiency - perfect for ECPs seeking an affordable and versatile OCT system. It’s ideal for
practices with limited staff since iScan80 delivers consistent scan acquisition with minimal training and
vocally guides patients through an entire exam in any of 12 languages.
The document summarizes the NewTom GO 2D/3D CEPH imaging system. It is an integrated 2D and 3D cephalometric imaging device that provides high resolution images with low radiation exposure. It features advanced imaging capabilities including panoramic, cephalometric, and CBCT imaging as well as connectivity to integration with practice management systems and third party software.
Medical Herb Identification and It’s BenefitsIRJET Journal
This document discusses medical herb identification and its benefits. It presents the methodology used for a project that aims to accurately identify a wide range of medicinal herbs using convolutional neural networks. The document provides background on medicinal herbs and their importance. It then describes the proposed workflow, which involves users registering and uploading images that are pre-processed and run through a CNN model for feature extraction and herb identification. Finally, the document reviews related work and concludes that understanding medical herb identification empowers people to take control of their health.
Who ever said advanced OCT scanning had to be complicated? When an OCT design puts user experience first, it can be simple to learn and easy to use. So it is with the Optovue iSeries. To be any easier they would have to run themselves—and sometimes they do!
But don’t confuse simplicity with performance. The iSeries systems are fully featured and deliver many exclusive Optovue capabilities such as ganglion cell complex (GCC) analysis with focal loss volume (FLV%) and global loss volume (GLV%) metrics, the iWellnessExam® and the Cornea Advance module, which includes Vault Mapping for specialty lens fitting. The iSeries also benefits from a large, ethnically diverse normative database.
Automatic Brain Tumor Segmentation on Multi-Modal MRI with Deep Neural NetworksAndrew Tsuei
This document describes a deep learning approach for automatic brain tumor segmentation on MRI scans. A convolutional neural network is trained on over 3 million patches from 220 glioma patients to classify voxels into tumor subclasses like enhancing tumor, necrosis, and edema. The trained model segments a new MRI scan with over 90% accuracy in under 20 minutes, significantly faster than manual segmentation by experts. This efficient and accurate segmentation technique could maximize treatment effectiveness while maintaining patient privacy in the cloud-based system.
IRJET- A Vision based Hand Gesture Recognition System using Convolutional...IRJET Journal
This document describes a vision-based hand gesture recognition system using convolutional neural networks. The system captures images of hand gestures using a camera, pre-processes the images, and classifies the gestures using a CNN model. The CNN architecture includes convolutional layers, max pooling layers, dropout layers, and fully connected layers. The system was trained on a dataset of images representing 7 different hand gestures. Testing achieved over 90% accuracy in recognizing the gestures. This vision-based approach allows for natural human-computer interaction without physical devices.
This document provides information about an upcoming workshop on sparse theory, applications, and signal processing. The workshop will cover topics including linear algebra, signal transforms, optimization algorithms, sparse representation theory, compressive sensing, and applications in areas like image processing, speech recognition, and medical imaging. Attendees will learn about open problems in the field, standard databases, performance metrics, and will receive training in MATLAB and LaTeX. The workshop aims to provide a forum for researchers and professionals to exchange ideas and advance knowledge in sparse representations and compressive sensing.
This document presents Jeevn-Net, a new neural network architecture for brain tumor segmentation and overall survival prediction. Jeevn-Net uses a cascaded U-Net structure with two U-Nets and applies auto-encoder regularization. It takes in MRI scans and outputs a segmented tumor image with extracted features. Random forest regression is then used to predict survival based on these features. The network achieves state-of-the-art performance for brain tumor segmentation and survival prediction.
The Eyestar 900 features swept-source technology, enabling precise measurement, as well as topographic assessment of the front and back corneal surface and the anterior chamber, including the lens, as well as imaging of all these structures. It also includes cornea-to-retina biometry of the entire eye.
This magazine issue of MAGNETOM Flash focuses on diffusion-weighted imaging applications. It includes articles on using DWI for prostate imaging at 3T, obtaining IVIM f-maps of pancreatic lesions, and monitoring therapy response for nonsecretory multiple myeloma. The issue also features new software version syngo MR B17 and its applications in oncology imaging such as syngo TimCT.
FPGA Implementation of Glaucoma Detection using Neural NetworksIRJET Journal
This document describes a study that implemented glaucoma detection using neural networks on an FPGA. The key steps were:
1. Features were extracted from retinal images including optic disk area, cup area, and neuro-retinal rim area. These features were used as inputs to the neural network.
2. A feedforward backpropagation neural network was trained to classify images as glaucoma or healthy based on the extracted features.
3. The neural network was implemented on a Spartan 3A FPGA to take advantage of its reconfigurability and parallel processing capabilities for neural networks.
4. Testing on sample images from a fundus image database achieved accurate classification of glaucoma and healthy
IRJET- Diversified Segmentation and Classification Techniques on Brain Tu...IRJET Journal
This document summarizes 20 research papers on techniques for detecting brain tumors using medical images like MRI scans. It discusses several techniques for image segmentation, feature extraction, and classification that have been used to automatically detect and diagnose brain tumors. The goal of the work is to consolidate these different techniques and provide new insights on recent approaches to brain tumor image processing. Key methods discussed include convolutional neural networks, random forest classifiers, discrete wavelet transforms, and probabilistic neural networks.
Digital image self-adaptive acquisition in medical x-ray imagingJie Bao
The document describes a method for digital self-adaptive image acquisition in medical x-ray imaging. It discusses x-ray fluoroscopy systems and the challenges of digital acquisition. The method uses digital subtraction to remove background signals, recognizes the valid imaging region, and analyzes the region's histogram to automatically set acquisition parameters like black level, white level, gain and offset for optimal image quality. An experiment validated that this approach improves image quality over traditional methods.
This document summarizes a technology roadmapping course on roadmapping concepts and applications. It includes sections on technology foresight, scenarios, trends and drivers, products and services, supporting systems, examples of technology roadmaps from various industries, and practical issues in roadmap design. The document also presents two case studies, one on a company's use of roadmapping for various business units and technologies, and another on Korea's national technology roadmapping process.
Does Over-Masturbation Contribute to Chronic Prostatitis.pptxwalterHu5
In some case, your chronic prostatitis may be related to over-masturbation. Generally, natural medicine Diuretic and Anti-inflammatory Pill can help mee get a cure.
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Histololgy of Female Reproductive System.pptxAyeshaZaid1
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2. Pourquoi utiliser la navigation en ORL?
· Une resection plus complète des tissus malades (ex: Polype) Le chirurgien peut
etre plus “agressif” avec une navigation
· Un taux de 2nd operation diminué
· Evite les complications chirurgicales
· Augmenter la sécurité et l´efficacité dans le geste
· Extrement utile si un repère anatomique a été enlevé lors d´une chirurgie
précédente
MAG 2008 Page 2
3. Sommaire
A propos de BrainLAB
Technologie et plateform
Logiciel de plannnification pre-opératoire
Logiciel de navigation per-opératoire
MAG 2008 Page 3
4. BrainLAB
• 3,000 hopitaux utilisant des logiciels
BrainLAB
• Clients dans plus de 75 pays
• 1000 employés dans 16 bureau de par
le monde
• 230 ingénieurs R&D
• 200 Ingénieurs services
• 3,300 Logiciels installés
• Plus de 350 installations en ORL et CMF
New BrainLAB headquarters in Feldkirchen near Munich
• Nouveau developpement pour la
plannification Maxilo facial depuis 2005
MAG 2008 Page 4
7. Debloquer les possibilités pour les patients et le staff
Oncologie
Neurochirurgie
Salle op integré
Rachis & Trauma
Orthopédie
Radiologie
Pharmaceutique
ORL
MAG 2008 Page 7
8. Imagerie Intra-operatoire– 1.5T iMRI
BrainSUITE® iMRI sallle d´opération integré
• Enregistrement automatisé du patient et transfert des scans inter-opératoires.
• Integration de la gestion des données et visualisation permettant d´améliorer le processus
de decision
• Opérations en dehors de la ligne de 5 Gauss utilisant des instruments chirurgicaux
normaux. MAG 2008 Page 8
10. Sommaire
A propos de BrainLAB
Technologie et plateform
Logiciel de plannnification pre-opératoire
Logiciel de navigation per-opératoire
MAG 2008 Page 10
11. Technologie a marqueurs passifs
Technique
• Camera envoie des signaux infrarouge
• Les spheres reflechissantes reflechis le signal
• La camera recoit le signal en retour
Votre bénéfice
• Localisation précise de tous les instruments sans erreur
• Pas de d´emmetteur ou recepteur supplémentaire
MAG 2008 Page 11
12. Platformes
Tous les systèmes utilisent
• Techonolgie avec marqueur passif
• Les memes fonctionalités logicielle
MAG 2008 Page 12
13. Sommaire
A propos de BrainLAB
Technologie et plateform
Logiciel de plannnification pre-opératoire
Logiciel de navigation per-opératoire
MAG 2008 Page 13
14. Logiciel de plannification pre-opératoire iPlan
1st step: Frankfort Horizontal
• Landmark based definition of Frankfort
Horizontal and Midsagital Plane in 2D
and 3D.
• Dataset is aligned to defined Planes
• Planes and Alignment necessary to be
able to mirror the segmented objects
from healthy to defect side
Benefit: Fast and easy definition of planes for mirroring and alignment of the
dataset
MAG 2008 Page 14
15. Logiciel de plannification pre-opératoire iPlan
2nd step: Segmentation of objects
• Several methods of Segmentation:
•Semiautomatic Segmentation
•Segmentation Slice by Slice with
Brush
•Usingof Seed Brush (segments
areas with same Houndfield units)
• Semi-automatic segmentation as
fastest option to segment bony
structures.
Benefit: Several options of segmentation depending on preferences and
indication.
MAG 2008 Page 15
16. Logiciel de plannification pre-opératoire iPlan
2nd step: Semiautomatic Segmentation
• Segmentation by definition of region of
interest in each view
• Only the red highlighted structures will
be segmented
• Changing of Houndsfield Units until
structures of interested are highlighted
red
Benefit: Most time saving and easiest option of Object Segmentation which
is superior over time consuming standard segmentation slice by slice
MAG 2008 Page 16
17. Logiciel de plannification pre-opératoire iPlan
3rd step: Mirroring of segmented objects
• Healthy side is used as template for
defect side.
• Object is mirrored at the prior defined
Midsagital plane
Benefit: Time saving creation of templates for reconstruction of defect side
MAG 2008 Page 17
18. Indication: Movement of fragments
Movement of copied objects
• The copied object can be moved in any
direction
• The movement is done in the 2D views
MAG 2008 Page 18
19. Résumé de la plannification pre-operatoire
• Semiautomatic Image Fusion – also for
postoperative control
• Definition of Midsagital
• Semiautomatic Segmentation
• Advanced Object Planning (Mirroring)
MAG 2008 Page 19
20. Particularité BrainLAB: La plannif maxilo faciale
• Frankfort Horizontal alignment brings the patient’s head in a natural position.
• In most cases only one part of the face is affected -so we can use the remaining
as a contour template. => Use of miroring function
• If both sides are affected, the Software can be used as planning tool for
repositioning of big fragments or to plan a model of an implant which can be
exported with a STL –Export (next Version).
• Another major field is implanting of dental. It is possible to plan them with trajectories
and dental implants can be imported and planned via STL-Import (next version)
• With iPlan CMFsurgeons can plan the intervention safe different states and come
back later for refinements.
• Now they can virtually plan the treatment or try out new reconstructive techniques
without touching the patient.
• With the support of an atlas they don‘t need to outline typical structures, iPlan makes
it as easy and fast as possible to generate a treatment template
• With the support of our navigation systems the reconstructions are more precise
and more accurate than before. Now the surgeon can operate in areas where that he
wouldn‘t have touched without the support of BrainLAB‘s advanced technology.
MAG 2008 Page 20
21. Workflow – 4 étapes pour la navigation per-opératoire
MAG 2008 Page 21
22. Sommaire
A propos de BrainLAB
Technologie et plateform
Logiciel de plannnification pre-opératoire
Navigation per-opératoire
MAG 2008 Page 22
23. Navigation per-operatoire
1st step: Preoperative Scan
• Utilization of preoperative scans –
no navigation scan necessary
• No fiducials necessary
Benefit: Reduction of radiation dose for patient
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24. Navigation per-operatoire
2nd step: Intraoperative preparation – Patient reference star
Non-invasive referencing with
headband - generally used for
sinus surgery in ENT
Minimal invasive referencing in
bone structure - generally used
for skull base surgery, lateral
indications or CMF cases
Benefit: Referencing according to needs and
indication.
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25. Navigation per-operatoire
3rd step: intraoperative registration
• Surface scanning with a laser
• No given registration points or registration routes
• Registration accomplished in one minute
• Registration possible in a sterile environment
Benefit: Touchless registration saves sterile environment.
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27. Navigation per-operatoire
4th step: Instrument integration
• Simple integration of all instruments
• Different geometries of stars and
adapter clamps fit on every
instrument
Benefit: Fast integration of every rigid instrument available in the OR
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29. Navigation per-operatoire
Advanced features
Eraser
Intraoperative Imaging
• Virtual anatomical update of structures
Ultrasound integration
• Tip of instrumentintegrated ultrasound
IGSonic as fully is tracked
device
• Removed tissue can be visualized
• virtually
Other imaging devices like C-arms
• First step to real intraoperative imaging
Benefit: From essential navigation to unlimited functionalities
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30. Résumé de la navigation per-opératoire
• Platforms according to needs
• Data acquisition
• Referencing
• Registration
• Navigation and Integration
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32. Conclusion
BrainLAB offre une solution pour la navigation et la plannification ORL
La plannification CMF est une option de la partie ORL
BrainLAB est le seul vendeur majeur proposant une véritable
plannification CMF, prenant en compte les implants
La plannification et la plateforme de navigation sont concues
pour recevoir d´autres spécialités (Neuro, ortho, Etc.)
MAG 2008 Page 32