5 papers
Shot Noise Reduction in Radiographic and Tomographic Multi-Channel Imaging with Self-Supervised Deep Learning
Yaroslav Zharov, Evelina Ametova, Rebecca Spiecker +3
Noise is an important issue for radiographic and tomographic imaging techniques. It becomes particularly critical in applications where additional constraints force a strong reduct…
Optimizing the Procedure of CT Segmentation Labeling
Yaroslav Zharov, Tilo Baumbach, Vincent Heuveline
In Computed Tomography, machine learning is often used for automated data processing. However, increasing model complexity is accompanied by increasingly large volume datasets, whi…
A Knowledge Distillation framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image
Jwalin Bhatt, Yaroslav Zharov, Sungho Suh +3
Morphological atlases are an important tool in organismal studies, and modern high-throughput Computed Tomography (CT) facilities can produce hundreds of full-body high-resolution…
Using the Order of Tomographic Slices as a Prior for Neural Networks Pre-Training
Yaroslav Zharov, Alexey Ershov, Tilo Baumbach +1
The technical advances in Computed Tomography (CT) allow to obtain immense amounts of 3D data. For such datasets it is very costly and time-consuming to obtain the accurate 3D segm…
Self-Supervised Learning for Biological Sample Localization in 3D Tomographic Images
Yaroslav Zharov, Alexey Ershov, Tilo Baumbach +1
In synchrotron-based Computed Tomography (CT) there is a trade-off between spatial resolution, field of view and speed of positioning and alignment of samples. The problem is even…