This document discusses a method called projectionGAN for removing missing cone artifacts from optical diffraction tomography (ODT) reconstructions using unsupervised deep learning. ODT suffers from low axial resolution and elongation artifacts due to the missing cone problem. ProjectionGAN trains a GAN to generate missing angular projections, which are then used in reconstruction to improve resolution and remove artifacts. Results on numerical phantoms, microbeads, and cells demonstrate projectionGAN effectively reduces elongation and produces sharper, more homogeneous reconstructions compared to conventional ODT.
Semi supervised, weakly-supervised, unsupervised, and active learningYusuke Uchida
An overview of semi supervised learning, weakly-supervised learning, unsupervised learning, and active learning.
Focused on recent deep learning-based image recognition approaches.
In this work, we introduce a new Markov operator associated with a digraph, which we refer to as a nonlinear Laplacian. Unlike previous Laplacians for digraphs, the nonlinear Laplacian does not rely on the stationary distribution of the random walk process and is well defined on digraphs that are not strongly connected. We show that the nonlinear Laplacian has nontrivial eigenvalues and give a Cheeger-like inequality, which relates the conductance of a digraph and the smallest non-zero eigenvalue of its nonlinear Laplacian. Finally, we apply the nonlinear Laplacian to the analysis of real-world networks and obtain encouraging results.
Semi supervised, weakly-supervised, unsupervised, and active learningYusuke Uchida
An overview of semi supervised learning, weakly-supervised learning, unsupervised learning, and active learning.
Focused on recent deep learning-based image recognition approaches.
In this work, we introduce a new Markov operator associated with a digraph, which we refer to as a nonlinear Laplacian. Unlike previous Laplacians for digraphs, the nonlinear Laplacian does not rely on the stationary distribution of the random walk process and is well defined on digraphs that are not strongly connected. We show that the nonlinear Laplacian has nontrivial eigenvalues and give a Cheeger-like inequality, which relates the conductance of a digraph and the smallest non-zero eigenvalue of its nonlinear Laplacian. Finally, we apply the nonlinear Laplacian to the analysis of real-world networks and obtain encouraging results.
Here is a Fujinon Binocular training presentation I created a few years back to explain some of the major differences and features of Fujinon Binoculars.
Jamel gantt- Know More About Computer GraphicsJamel Gantt
Jamel Gantt has the abilities to report images to increase magazine and commercial techniques. She knows that many of us are distressing when expert with obtaining our photo acquired, but he has a capability of easily placing people at comfort to provide excellent, normal images.
Presentation for Science and research where it could be so beneficial for those who interested in such topics, the presentation is about x-ray diffraction but with new method that use Fourier mathematical to converts fourth and back
Rad 206 p11 Fundamentals of Imaging - Control of Scatter Radiationsehlawi
Fundamentals of Imaging
This course will provide you with the principles involved in the formation and recording of the radiologic image in both conventional and digital imaging systems as well as the principles of image quality assessment.
Control of Scatter Radiation
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Missing cone artifact removal in odt using unsupervised deep learning in the projection domain
1. Missing Cone Artifact Removal in ODT Using
Unsupervised Deep Learning in the Projection
Domain
BISPL - BioImaging, Signal Processing,
and Learning lab.
KAIST, Korea
2. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Optical Diffraction Tomography
Measures 3D refractive index with optical illumination
Reconstruction through field-retrieval (Fourier diffraction theorem)
GP used to enhance resolution
2
3. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Missing cone prblem
3
… …
𝑘𝑚, 𝑘𝑛
𝑘𝑝
Measurement
(hologram)
Problem arising in diffraction tomography
• Low axial resolution, elongation in the optical axes
Fourier
Diffraction
theorem
4. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Missing cone prblem
4
… …
𝑘𝑚, 𝑘𝑛
𝑘𝑝
Measurement
(hologram)
Problem arising in diffraction tomography
• Low axial resolution, elongation in the optical axes
Fourier
Diffraction
theorem
5. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Missing cone prblem
5
… …
𝑘𝑚, 𝑘𝑛
𝑘𝑝
Measurement
(hologram)
Problem arising in diffraction tomography
• Low axial resolution, elongation in the optical axes
Fourier
Diffraction
theorem
6. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Missing cone prblem
6
… …
𝑘𝑚, 𝑘𝑛
𝑘𝑝
Measurement
(hologram)
Missing cone
Missing cone problem in 3D
Problem arising in diffraction tomography
• Low axial resolution, elongation in the optical axes
7. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Missing cone prblem
7
Low resolution
Problem arising in diffraction tomography
• Low axial resolution, elongation in the optical axes
8. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Research Motivation
8
Parallel-ray
projections
gp-reconstruction Close relationship btw. non-diffraction / diffraction tomography
Approximation possible!
9. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Research Motivation
9
Parallel-ray
projections
gp-reconstruction Close relationship btw. non-diffraction / diffraction tomography
• Projections aligned w. measurement angle: high resolution
• Projections un-aligned w. measurement angle: low resolution
𝒴Ω
10. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Research Motivation
10
Parallel-ray
projections
gp-reconstruction Close relationship btw. non-diffraction / diffraction tomography
• Projections aligned w. measurement angle: high resolution
• Projections un-aligned w. measurement angle: low resolution
𝒴Ω 𝒴Ωc
11. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Research Motivation
11
Parallel-ray
projections
gp-reconstruction Close relationship btw. non-diffraction / diffraction tomography
• Projections aligned w. measurement angle: high resolution
• Projections un-aligned w. measurement angle: low resolution
𝒴Ω 𝒴Ωc
projectionGAN
0° 20° 40° 80° 100°
60°
12. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
projectionGAN
Field-retrieval
GP-reconstruction
… …
1st 23th 49th
Cell
Source
Incident Wave
Diffracted
Wave
Measured
Hologram
1. Reconstruction
12
13. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
projectionGAN
Field-retrieval
GP-reconstruction
… …
1st 23th 49th
Cell
Source
Incident Wave
Diffracted
Wave
TomoGAN
Final reconstruction
X-ray transform
𝜔1 𝜔2 𝜔3 𝜔4 𝜔5
𝜔1 𝜔2 𝜔3 𝜔4 𝜔5
FBP
Measured
Hologram
13
2. projectionGAN
1. Reconstruction
14. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Results: numerical simulation
14
Elongation
False signal
projectionGAN
15. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Results: microbead
15
Missing cone
Inhomogeneous
shape
RI (True: 1.46)
projectionGAN
16. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Results: biological cells
16
17. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Results: biological cells
17
18. Part I: Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
Results: biological cells
18
