Michał Byra

1.9k total citations
42 papers, 1.3k citations indexed

About

Michał Byra is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michał Byra has authored 42 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Artificial Intelligence and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michał Byra's work include AI in cancer detection (17 papers), Ultrasound Imaging and Elastography (15 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Michał Byra is often cited by papers focused on AI in cancer detection (17 papers), Ultrasound Imaging and Elastography (15 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Michał Byra collaborates with scholars based in Poland, United States and Japan. Michał Byra's co-authors include Andrzej Nowicki, Michael P. André, Katarzyna Dobruch‐Sobczak, Hanna Piotrzkowska‐Wróblewska, Linda K. Olson, Michael Y. Galperin, Haydee Ojeda‐Fournier, Christopher Comstock, M K O'Boyle and Piotr Jarosik and has published in prestigious journals such as Scientific Reports, Radiology and The Journal of the Acoustical Society of America.

In The Last Decade

Michał Byra

40 papers receiving 1.3k citations

Peers

Countries citing papers authored by Michał Byra

Since Specialization

Citations

This map shows the geographic impact of Michał Byra's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michał Byra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michał Byra more than expected).

Fields of papers citing papers by Michał Byra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michał Byra. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michał Byra. The network helps show where Michał Byra may publish in the future.

Co-authorship network of co-authors of Michał Byra

This figure shows the co-authorship network connecting the top 25 collaborators of Michał Byra. A scholar is included among the top collaborators of Michał Byra based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michał Byra. Michał Byra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	A new family of instance-level loss functions for improving instance-level segmentation and detection of white matter hyperintensities in routine clinical brain MRI 2024 ·Computers in Biology and Medicine ·Muhammad Febrian Rachmadi, Michał Byra, Henrik Skibbe	3
2	Implicit Neural Representations for Speed-of-Sound Estimation in Ultrasound 2024 ·Michał Byra, Piotr Jarosik, (unknown), Ziemowit Klimonda, Marcin Lewandowski	0
3	Exploring the performance of implicit neural representations for brain image registration 2023 ·Scientific Reports ·Michał Byra, Charissa Poon, Muhammad Febrian Rachmadi, (unknown), Henrik Skibbe	3
4	BUS‐Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets 2023 ·Medical Physics ·(unknown), Michał Byra, Robert Martí, Moi Hoon Yap, Reyer Zwiggelaar	12
5	Ultrasound and biomarker based assessment of hepatic steatosis in patients with severe obesity 2022 ·Polskie Archiwum Medycyny Wewnętrznej ·Michał Byra, Cezary Szmigielski, Piotr Kalinowski, Rafał Paluszkiewicz, Bogna Ziarkiewicz‐Wróblewska, Krzysztof Zieniewicz, Grzegorz Styczyński	2
6	Prediction of response to neoadjuvant chemotherapy in breast cancer with recurrent neural networks and raw ultrasound signals 2022 ·Physics in Medicine and Biology ·Michał Byra, Katarzyna Dobruch‐Sobczak, Hanna Piotrzkowska‐Wróblewska, Ziemowit Klimonda, Jerzy Litniewski	6
7	Explaining a deep learning based breast ultrasound image classifier with saliency maps 2022 ·Journal of Ultrasonography ·Michał Byra, Katarzyna Dobruch‐Sobczak, Hanna Piotrzkowska‐Wróblewska, Ziemowit Klimonda, Jerzy Litniewski	9
8	Unsupervised deep learning based approach to temperature monitoring in focused ultrasound treatment 2022 ·Ultrasonics ·Michał Byra, Ziemowit Klimonda, (unknown), Barbara Gambin	7
9	Joint segmentation and classification of breast masses based on ultrasound radio-frequency data and convolutional neural networks 2022 ·Ultrasonics ·Michał Byra, Piotr Jarosik, Katarzyna Dobruch‐Sobczak, Ziemowit Klimonda, Hanna Piotrzkowska‐Wróblewska, Jerzy Litniewski, Andrzej Nowicki	22
10	The Influence of Surgical Weight Reduction on Left Atrial Strain 2021 ·Obesity Surgery ·(unknown), Piotr Kalinowski, Krzysztof Zieniewicz, Cezary Szmigielski, Michał Byra, Grzegorz Styczyński	7
11	Breast mass classification with transfer learning based on scaling of deep representations 2021 ·Biomedical Signal Processing and Control ·Michał Byra	54
12	Pixel-Wise Deep Reinforcement Learning Approach for Ultrasound Image Denoising 2021 ·Piotr Jarosik, Marcin Lewandowski, Ziemowit Klimonda, Michał Byra	10
13	Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat with Radiofrequency Ultrasound Data Using One-dimensional Convolutional Neural Networks 2020 ·Radiology ·Aiguo Han, Michał Byra, Elhamy Heba, Michael P. André, John W. Erdman, Rohit Loomba, Claude B. Sirlin, William D. O’Brien	99
14	Breast lesion classification based on ultrasonic radio-frequency signals using convolutional neural networks 2020 ·Journal of Applied Biomedicine ·Piotr Jarosik, Ziemowit Klimonda, Marcin Lewandowski, Michał Byra	20
15	Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network 2020 ·Biomedical Signal Processing and Control ·Michał Byra, Piotr Jarosik, (unknown), Michael Y. Galperin, Haydee Ojeda‐Fournier, Linda K. Olson, M K O'Boyle, Christopher Comstock, Michael P. André	211
16	Assessment of an in vitro model of rotator cuff degeneration using quantitative magnetic resonance and ultrasound imaging with biochemical and histological correlation 2019 ·European Journal of Radiology ·(unknown), Yajun Ma, Rachel High, (unknown), Jonathan Wong, Michał Byra, Adam C. Searleman, (unknown), Lidi Wan, Nicole K. Le, Jiang Du, Eric Y. Chang	9
17	Quantitative Ultrasound and B-Mode Image Texture Features Correlate with Collagen and Myelin Content in Human Ulnar Nerve Fascicles 2019 ·Ultrasound in Medicine & Biology ·Michał Byra, Lidi Wan, Jonathan Wong, Jiang Du, Sameer B. Shah, Michael P. André, Eric Y. Chang	21
18	Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images 2018 ·International Journal of Computer Assisted Radiology and Surgery ·Michał Byra, Grzegorz Styczyński, Cezary Szmigielski, Piotr Kalinowski, Łukasz Michałowski, Rafał Paluszkiewicz, Bogna Ziarkiewicz‐Wróblewska, Krzysztof Zieniewicz, Piotr Sobieraj, Andrzej Nowicki	197
19	Classification of breast lesions using segmented quantitative ultrasound maps of homodyned K distribution parameters 2016 ·Medical Physics ·Michał Byra, Andrzej Nowicki, Hanna Piotrzkowska‐Wróblewska, Katarzyna Dobruch‐Sobczak	45
20	Temperature detection based on nonparametric statistics of ultrasound echoes 2015 ·Hydroacoustics ·Michał Byra, Barbara Gambin	3

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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