COMPUTING THE GROWTH RATE OF STEM CELLS USING DIGITAL IMAGE PROCESSING Pratyusha Mahavadi
The aim is to compute the growth rate of stem cells by using segmentation, feature extraction and pattern recognition which are the fundamental methods of digital image processing. DRLSE algorithm is applied for segmenting images. The DRLSE algorithm is an amalgamation of Canny Edge Detector algorithm and DRLSE method, which uses the four well potential function. Features are extracted from segmented images using GLCM method and finally Support Vector Machine (SVM) is used for pattern recognition and classification of stem cells.
DEVELOPING CRYO-ELECTRON MICROSCOPY OF BIOMOLECULES IN WATERGuttiPavan
Cryo-electron microscopy (Cryo-EM) is a type of transmission electron microscopy that allows for the specimen of interest to be viewed at cryogenic temperatures (-150°C)
Following years of improvement, the cryo-electron microscope has become a valuable tool for viewing and studying the 3D structures of various biological molecules in water.
COMPUTING THE GROWTH RATE OF STEM CELLS USING DIGITAL IMAGE PROCESSING Pratyusha Mahavadi
The aim is to compute the growth rate of stem cells by using segmentation, feature extraction and pattern recognition which are the fundamental methods of digital image processing. DRLSE algorithm is applied for segmenting images. The DRLSE algorithm is an amalgamation of Canny Edge Detector algorithm and DRLSE method, which uses the four well potential function. Features are extracted from segmented images using GLCM method and finally Support Vector Machine (SVM) is used for pattern recognition and classification of stem cells.
DEVELOPING CRYO-ELECTRON MICROSCOPY OF BIOMOLECULES IN WATERGuttiPavan
Cryo-electron microscopy (Cryo-EM) is a type of transmission electron microscopy that allows for the specimen of interest to be viewed at cryogenic temperatures (-150°C)
Following years of improvement, the cryo-electron microscope has become a valuable tool for viewing and studying the 3D structures of various biological molecules in water.
in the name of GOD
in this slides we express about tfts and retina.
and then express how people who is blinde can see with retina.
this project have many picture about its topics and express them.
more chemistry contents are available
1. pdf file on Termmate: https://www.termmate.com/rabia.aziz
2. YouTube: https://www.youtube.com/channel/UCKxWnNdskGHnZFS0h1QRTEA
3. Facebook: https://web.facebook.com/Chemist.Rabia.Aziz/
4. Blogger: https://chemistry-academy.blogspot.com/
Nobel Prize in Chemistry 2017
Joachim Frank
Cryo-Electron Microscopy
Different types of Nanolithography technique.
Types: Electron beam lithography, Photolithography, electron-beam writing, ion- lithography, X-ray lithography, and related images, concepts and graphical views.
I hope this presentation helpful for you.
https://www.linkedin.com/in/preeti-choudhary-266414182/
https://www.instagram.com/chaudharypreeti1997/
https://www.facebook.com/profile.php?id=100013419194533
https://twitter.com/preetic27018281
Please like, share, comment and follow.
stay connected
If any query then contact:
chaudharypreeti1997@gmail.com
Thanking-You
Preeti Choudhary
Artifact Detection and Removal from In-Vivo Neural SignalsMd Kafiul Islam
Background
In vivo neural recordings are often corrupted by different artifacts, especially in a less-constrained recording environment. Due to limited understanding of the artifacts appeared in the in vivo neural data, it is more challenging to identify artifacts from neural signal components compared with other applications. The objective of this work is to analyze artifact characteristics and to develop an algorithm for automatic artifact detection and removal without distorting the signals of interest.
New method
The proposed algorithm for artifact detection and removal is based on the stationary wavelet transform with selected frequency bands of neural signals. The selection of frequency bands is based on the spectrum characteristics of in vivo neural data. Further, to make the proposed algorithm robust under different recording conditions, a modified universal-threshold value is proposed.
Results
Extensive simulations have been performed to evaluate the performance of the proposed algorithm in terms of both amount of artifact removal and amount of distortion to neural signals. The quantitative results reveal that the algorithm is quite robust for different artifact types and artifact-to-signal ratio.
Comparison with existing methods
Both real and synthesized data have been used for testing the proposed algorithm in comparison with other artifact removal algorithms (e.g. ICA, wICA, wCCA, EMD-ICA, and EMD-CCA) found in the literature. Comparative testing results suggest that the proposed algorithm performs better than the available algorithms.
Conclusion
Our work is expected to be useful for future research on in vivo neural signal processing and eventually to develop a real-time neural interface for advanced neuroscience and behavioral experiments.
3D-UTE Rosette MRI and MRSI at UHF human (7T) and animal scanners (9.4T) usin...Uzay Emir
#ismrm #ISMRM2022 #ISMRM22
3D-UTE Rosette Applications (MRI and MRSI) at UHF human (7T) and animal scanners (9.4T) using The Berkeley Advanced Reconstruction Toolbox (BART) toolbox
Uzay Emir
Afternoon Tea with BART
Time: 15:45-16:45
Unsupervised Deconvolution Neural Network for High Quality Ultrasound ImagingShujaat Khan
High quality US imaging demand large number of measurements that can increase the cost, size and power requirements. Therefore, low-powered, portable and 3D ultrasound imaging system require reconstruction algorithms that can produce high quality images using fewer receive measurements. Number of model specific methods has been proposed which doesn't work under perturbation. For instance, compressive deconvolution ultrasound which provide a reasonable quality with limited measurements however, it has its own down-sides such as high computation cost and accurate estimation of point spread function (PSF). An other major limitation of conventional methods is that they require RF or base-band signal which is difficult to obtain from portable US systems. To deal with the aforementioned issues, in this study we designed a novel deep deconvolution model for image domain-based deconvolution. The proposed deep deconvolution (DeepDeconv) model can be trained in an unsupervised fashion, alleviate the need of paired high and low quality images. The model was evaluated on both the phantom and in-vivo scans for various sampling configurations. The proposed DeepDeconv significantly enhance the details of anatomical structures and using unsupervised learning on average it achieved 2.14dB, 4.96dB and 0.01 units gain in CR, PSNR and SSIM values respectively, which are comparable to the supervised method.
in the name of GOD
in this slides we express about tfts and retina.
and then express how people who is blinde can see with retina.
this project have many picture about its topics and express them.
more chemistry contents are available
1. pdf file on Termmate: https://www.termmate.com/rabia.aziz
2. YouTube: https://www.youtube.com/channel/UCKxWnNdskGHnZFS0h1QRTEA
3. Facebook: https://web.facebook.com/Chemist.Rabia.Aziz/
4. Blogger: https://chemistry-academy.blogspot.com/
Nobel Prize in Chemistry 2017
Joachim Frank
Cryo-Electron Microscopy
Different types of Nanolithography technique.
Types: Electron beam lithography, Photolithography, electron-beam writing, ion- lithography, X-ray lithography, and related images, concepts and graphical views.
I hope this presentation helpful for you.
https://www.linkedin.com/in/preeti-choudhary-266414182/
https://www.instagram.com/chaudharypreeti1997/
https://www.facebook.com/profile.php?id=100013419194533
https://twitter.com/preetic27018281
Please like, share, comment and follow.
stay connected
If any query then contact:
chaudharypreeti1997@gmail.com
Thanking-You
Preeti Choudhary
Artifact Detection and Removal from In-Vivo Neural SignalsMd Kafiul Islam
Background
In vivo neural recordings are often corrupted by different artifacts, especially in a less-constrained recording environment. Due to limited understanding of the artifacts appeared in the in vivo neural data, it is more challenging to identify artifacts from neural signal components compared with other applications. The objective of this work is to analyze artifact characteristics and to develop an algorithm for automatic artifact detection and removal without distorting the signals of interest.
New method
The proposed algorithm for artifact detection and removal is based on the stationary wavelet transform with selected frequency bands of neural signals. The selection of frequency bands is based on the spectrum characteristics of in vivo neural data. Further, to make the proposed algorithm robust under different recording conditions, a modified universal-threshold value is proposed.
Results
Extensive simulations have been performed to evaluate the performance of the proposed algorithm in terms of both amount of artifact removal and amount of distortion to neural signals. The quantitative results reveal that the algorithm is quite robust for different artifact types and artifact-to-signal ratio.
Comparison with existing methods
Both real and synthesized data have been used for testing the proposed algorithm in comparison with other artifact removal algorithms (e.g. ICA, wICA, wCCA, EMD-ICA, and EMD-CCA) found in the literature. Comparative testing results suggest that the proposed algorithm performs better than the available algorithms.
Conclusion
Our work is expected to be useful for future research on in vivo neural signal processing and eventually to develop a real-time neural interface for advanced neuroscience and behavioral experiments.
3D-UTE Rosette MRI and MRSI at UHF human (7T) and animal scanners (9.4T) usin...Uzay Emir
#ismrm #ISMRM2022 #ISMRM22
3D-UTE Rosette Applications (MRI and MRSI) at UHF human (7T) and animal scanners (9.4T) using The Berkeley Advanced Reconstruction Toolbox (BART) toolbox
Uzay Emir
Afternoon Tea with BART
Time: 15:45-16:45
Unsupervised Deconvolution Neural Network for High Quality Ultrasound ImagingShujaat Khan
High quality US imaging demand large number of measurements that can increase the cost, size and power requirements. Therefore, low-powered, portable and 3D ultrasound imaging system require reconstruction algorithms that can produce high quality images using fewer receive measurements. Number of model specific methods has been proposed which doesn't work under perturbation. For instance, compressive deconvolution ultrasound which provide a reasonable quality with limited measurements however, it has its own down-sides such as high computation cost and accurate estimation of point spread function (PSF). An other major limitation of conventional methods is that they require RF or base-band signal which is difficult to obtain from portable US systems. To deal with the aforementioned issues, in this study we designed a novel deep deconvolution model for image domain-based deconvolution. The proposed deep deconvolution (DeepDeconv) model can be trained in an unsupervised fashion, alleviate the need of paired high and low quality images. The model was evaluated on both the phantom and in-vivo scans for various sampling configurations. The proposed DeepDeconv significantly enhance the details of anatomical structures and using unsupervised learning on average it achieved 2.14dB, 4.96dB and 0.01 units gain in CR, PSNR and SSIM values respectively, which are comparable to the supervised method.
Real Time Human Posture Detection with Multiple Depth SensorsWassim Filali
This thesis presents a comprehensive study of the state-of-the-art in human posture reconstruction, its contexts, and associated applications. The underlying research focuses on utilization of computer vision techniques for human activity recognition based on embedded system technologies and intelligent camera systems. It also focuses on human posture reconstruction as it plays a key role in subsequent activity recognition. In this work, we have relied on the latest technological advances in sensor technology, specifically on the advent of Kinect, an RGB-D sensor from Microsoft, to realize a low-level sensor fusion algorithm to fuse the outputs of multiple depth sensors for human posture reconstruction.
In this endeavor, the different challenges encountered are: (1) occlusions when using a single sensor; (2) the combinatorial complexity of learning a high dimensional space corresponding to human postures; and finally, (3) embedded systems constraints. The proposed system addresses and consequently resolves each of these challenges.
The fusion of multiple depth sensors gives better result than individual sensors as the fusion alleviates the majority of occlusions by resolving many incoherencies thus by guaranteeing improved robustness and completeness on the observed scene. In this manuscript, we have elaborated the low-level fusion strategy which makes up the main contribution of this thesis. We have adopted a learning technique based on decision forests. Our algorithm is applied on our own learning dataset acquired with our multi-platform kinect coupled to a commercial motion capture system.
The two main principal features are sensor data fusion and supervised learning. Specifically, the data fusion technique is described by acquisition, segmentation, and voxelization which generates a 3D reconstruction of the occupied space. The supervised learning is based on decision forests and uses appropriate descriptors extracted from the reconstructed data. Various experiments including specific parameter learning (tuning) runs have been realized.
Qualitative and quantitative comparative human articulation reconstruction precision evaluations against the state-of-the-art strategies have also been carried out.
The different algorithms have been implemented on a personal computer environment which helped to analyze the essential parts that needs hardware embedded integration. The hardware integration consisted of studying and comparing multiple approaches. FPGA is a platform that meets both the performance and embeddability criteria as it provides resources that reduce CPU cost. This allowed us to make a contribution which constitutes a hierarchically prioritized design via a layer of intermediary modules. Comparative studies have also been done using background subtraction implementation as a benchmark integrated on PC, GPU, and FPGA (the FPGA implementation has been presented in detail).
A MEMS BASED OPTICAL COHERENCE TOMOGRAPHY IMAGING SYSTEM AND OPTICAL BIOPSY P...Ping Hsu
A fully-functional, real-time optical coherence tomography (OCT) system based on a high-speed, gimbal-less micromachined scanning
mirror is presented. The designed MEMS control architecture allows the MEMS based imaging probes to be connected to a time-domain, a
Fourier domain or a spectral domain OCT system. Furthermore, a variety of probes optimized for specific laboratory or clinical
applications including various minimally invasive endoscopic, handheld or lab-bench mounted probes may be switched between effortlessly
and important driving parameters adjusted in real-time. In addition, artifact free imaging speeds of 33μs per voxel have been achieved
while imaging a 1.4mm×1.4mm×1.4mm region with 5μm×5μm×5μm sampling resolution (SD-OCT system.)
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
1. Steve Ludtke
Charles C. Bell Professor
Biochemistry and Molecular Biology
Director, CryoEM/CryoET Core
Co-director CIBR Center
Baylor College of Medicine
Tomography, Subtomogram Averaging
and the Next Steps
4. STORM Imaging of Prochlorococcus FtsZ Ring
Liu R, Liu Y, Liu S, Wang Y, Li K, Li N, et al. Three-Dimensional Superresolution Imaging of the FtsZ Ring during
Cell Division of the Cyanobacterium Prochlorococcus. Giovannoni SJ, editor. MBio; 2017 Nov 21;8(6):834.
PMCID: PMC5698547
14. Dai, W., et.al., (2018).Visualizing Individual RuBisCO and Its Assembly into Carboxysomes in Marine
Cyanobacteria by Cryo-Electron Tomography. JMB. 430:4156-4167.
18. Y Z
(bin x2)
3 Iterations
Refined
landmarks
Final aligned tiltseries X X
Runtime:
~10 minutes on
12 threads
X Shi,
Z Wang,
BCM
19. Tilt series alignment
3D Reconstruction
Pick landmarks (3D)
Coarse alignment
Bin by
8x
4x
2x
1xRefine landmark
coordinates
Refine alignent
parameters
Start:
Unaligned
tiltseries
Landmarks
Top view
Side view
coarse align
Side view
iteration #4 Tomogram slice view
Toxoplasma gondii
Stella Y. Sun
~5-10 min total per tomogram
21. Reconstruction via tiled direct Fourier inversion
• Reconstruction via tiled direct Fourier inversion
• Normally only generate 1K or 2K reconstructions
-> for visualization and annotation
35. Per-particle, per-tilt CTF correction
Determine defocus range from
near-0° tilts with more signal
max(Δz)
min(Δz)
avg(Δz) = center of ice
Search within defocus range
at higher tilt angles.
e-
avg(Δz)
tilt angle (θ)
ptcl(Δz)
center
of ice
θ
e-
36. EMD-5592 - 6ÅEMD-3420 - 11Å Unpublished - 9Å
High-resolution subtomogram averaging in EMAN2
Hi-res Single Particle 3D SPT – EMAN23D SPT - PyTom
EMPIAR – 10064
80S Ribosome
37. Per-particle, per-tilt use cases:
in situ?
• Lower resolution (~20Å)
• Content above & below sample
in vitro
• Thin, purified samples
• Higher resolution (<10Å)
39. Future Directions
• Software now permits high resolution refinement, data collection protocols
need to be optimized!
• larger tilt step?
• narrower tilt range?
• Play with dose distribution?
• Movie-mode imaging -> ~1 e-/Å2 split into 10 or 20 frames!
• How much interference do we get from the cell with per-particle tilt series?
• Particle variability in cells (compositional and conformational)
• I want a Dual-beam Cryo-FIB!
40. Acknowledgements
PC12 Neurite
Wei Dai (NCMI→Rutgers)
Trypanosome
Stella Sun (SLAC)
Cynthia He (NUS)
Mouse Neurite
Patrick Mitchell (SLAC)
Gong-her Wu (SLAC)Muyuan Chen James M. Bell
Wah Chiu, Mike Schmid (SLAC)
Chen, M., Dai, W., Sun, S.Y., Jonasch, D., He, C.Y., Schmid, M.F., Chiu, W. & Ludtke, S.J.,
2017, Convolutional neural networks for automated annotation of cellular cryo-electron
tomograms, Nature methods.
We thank the NIH for its
support: R01GM080139,
R01GM072804,
P41GM103832, and also
grants from the AHA and MDA.
E.coli TolC
X. Shi (BCM)
Zhao Wang (BCM)
