Debesh Jha
Impact in
- Health Informatics top 2%
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
Papers in
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- Radiomics and Machine Learning in Medical Imaging 26
- COVID-19 diagnosis using AI 9
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- Advanced Neural Network Applications 12
- Medical Image Segmentation Techniques 10
- Co-authors
- Pål Halvorsen (23 shared papers)Michael Alexander Riegler (21 shared papers)Håvard D. Johansen (14 shared papers)Nikhil Kumar Tomar (21 shared papers)Sharib Ali (10 shared papers)Ulaş Bağcı (43 shared papers)Dag Johansen (14 shared papers)Goo‐Rak Kwon (10 shared papers)
- Journals
- Medical Image Analysis (5 papers)Lecture notes in computer science (22 papers)Alzheimer s & Dementia (2 papers)Scientific Reports (2 papers)Artificial Intelligence in Medicine (1 paper)
- Partner nations
- United StatesNorwayIndia
In The Last Decade
Debesh Jha
84 papers receiving 2.1k citations
Debesh Jha's Hit Papers
Peers
Comparison fields: 5 of 112
- Health Informatics 67
- Computer Vision and Pattern Recognition 831
- Radiology, Nuclear Medicine and Imaging 730
- Neurology 259
- Oncology 607
Countries citing papers authored by Debesh Jha
This map shows the geographic impact of Debesh Jha'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 Debesh Jha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debesh Jha more than expected).
Fields of papers citing papers by Debesh Jha
This network shows the impact of papers produced by Debesh Jha. 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 Debesh Jha. The network helps show where Debesh Jha may publish in the future.
Co-authors
The 25 scholars most cited alongside Debesh Jha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning Hit paper breakdown → | 2021 | 288 |
| 2 | A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation Hit paper breakdown → | 2021 | 254 |
| 3 | FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation Hit paper breakdown → | 2022 | 192 |
| 4 | 2023 | 180 | |
| 5 | 2022 | 135 | |
| 6 | 2021 | 104 | |
| 7 | 2017 | 83 | |
| 8 | 2020 | 68 | |
| 9 | 2021 | 67 | |
| 10 | 2022 | 58 | |
| 11 | 2019 | 46 | |
| 12 | 2020 | 43 | |
| 13 | 2020 | 42 | |
| 14 | 2021 | 37 | |
| 15 | 2020 | 35 | |
| 16 | 2024 | 34 | |
| 17 | 2018 | 33 | |
| 18 | 2023 | 31 | |
| 19 | 2024 | 31 | |
| 20 | 2021 | 29 |
About Debesh Jha
Debesh Jha is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Oncology, Artificial Intelligence and Neurology, having authored 91 papers that have together received 2.2k indexed citations. Recurring topics across this work include Colorectal Cancer Screening and Detection (27 papers), Radiomics and Machine Learning in Medical Imaging (26 papers), AI in cancer detection (23 papers), Brain Tumor Detection and Classification (13 papers), Advanced Neural Network Applications (12 papers), Medical Image Segmentation Techniques (10 papers), COVID-19 diagnosis using AI (9 papers) and Gastrointestinal Bleeding Diagnosis and Treatment (7 papers). The work is most often cited by research in Health Informatics (67 citations), Computer Vision and Pattern Recognition (831 citations), Radiology, Nuclear Medicine and Imaging (730 citations), Neurology (259 citations) and Oncology (607 citations). Debesh Jha has collaborated with scholars based in United States, Norway and India. Frequent co-authors include Pål Halvorsen, Michael Alexander Riegler, Håvard D. Johansen, Nikhil Kumar Tomar, Sharib Ali, Ulaş Bağcı, Dag Johansen, Goo‐Rak Kwon, Jens Rittscher and Thomas de Lange. Their work appears in journals such as Medical Image Analysis, Lecture notes in computer science, Alzheimer s & Dementia, Scientific Reports and Artificial Intelligence in Medicine.
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.