150 citations · 424 across the 27 of their papers we have counts for
6 papers · 1 filter
Self-supervised Physics-based Denoising for Computed Tomography
Elvira Zainulina, Alexey Chernyavskiy, Dmitry V. Dylov
Computed Tomography (CT) imposes risk on the patients due to its inherent X-ray radiation, stimulating the development of low-dose CT (LDCT) imaging methods. Lowering the radiation…
Medical Image Captioning via Generative Pretrained Transformers
Alexander Selivanov, Oleg Y. Rogov, Daniil Chesakov +3
The automatic clinical caption generation problem is referred to as proposed model combining the analysis of frontal chest X-Ray scans with structured patient information from the…
PyTorch Image Quality: Metrics for Image Quality Assessment
Sergey Kastryulin, Jamil Zakirov, Denis Prokopenko +1
Image Quality Assessment (IQA) metrics are widely used to quantitatively estimate the extent of image degradation following some forming, restoring, transforming, or enhancing algo…
Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging
Ivan Zakazov, Vladimir Shaposhnikov, Iaroslav Bespalov +1
Generalizability of deep learning models may be severely affected by the difference in the distributions of the train (source domain) and the test (target domain) sets, e.g., when…
Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging
Ekaterina Kuzmina, Artem Razumov, Oleg Y. Rogov +3
Image corruption by motion artifacts is an ingrained problem in Magnetic Resonance Imaging (MRI). In this work, we propose a neural network-based regularization term to enhance Aut…
Image Quality Assessment for Magnetic Resonance Imaging
Segrey Kastryulin, Jamil Zakirov, Nicola Pezzotti +1
Image quality assessment (IQA) algorithms aim to reproduce the human's perception of the image quality. The growing popularity of image enhancement, generation, and recovery models…