Ulaş Bağcı

9.8k total citations · 2 hit papers
217 papers, 4.2k citations indexed

About

Ulaş Bağcı is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Ulaş Bağcı has authored 217 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Radiology, Nuclear Medicine and Imaging, 66 papers in Computer Vision and Pattern Recognition and 45 papers in Artificial Intelligence. Recurrent topics in Ulaş Bağcı's work include Radiomics and Machine Learning in Medical Imaging (67 papers), Medical Image Segmentation Techniques (37 papers) and AI in cancer detection (36 papers). Ulaş Bağcı is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (67 papers), Medical Image Segmentation Techniques (37 papers) and AI in cancer detection (36 papers). Ulaş Bağcı collaborates with scholars based in United States, Türkiye and United Kingdom. Ulaş Bağcı's co-authors include Daniel J. Mollura, Ziyue Xu, Jayaram K. Udupa, Brent Foster, Xinjian Chen, Awais Mansoor, Jianhua Yao, Georgios Z. Papadakis, Sarfaraz Hussein and Michael B. Wallace and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.

In The Last Decade

Ulaş Bağcı

195 papers receiving 4.1k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8

2023 121 citations Ulaş Bağcı et al. profile →
Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

2024 105 citations Reza Azad, Yury Velichko et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Ulaş Bağcı	2.1k	1.2k	934	809	636	217	4.2k
Takeshi Hara	2.2k 1.0×	1.1k 1.0×	901 1.0×	733 0.9×	795 1.3×	327	5.5k
Rikiya Yamashita	1.6k 0.8×	638 0.6×	1.1k 1.2×	390 0.5×	499 0.8×	49	4.1k
Arunachalam Narayanaswamy	3.0k 1.4×	852 0.7×	1.2k 1.3×	365 0.5×	433 0.7×	15	5.3k
Mizuho Nishio	1.8k 0.9×	665 0.6×	1.0k 1.1×	725 0.9×	563 0.9×	67	4.3k
Mingchen Gao	1.8k 0.8×	1.4k 1.2×	1.8k 2.0×	532 0.7×	537 0.8×	54	4.8k
Hoo-Chang Shin	1.9k 0.9×	1.4k 1.2×	2.0k 2.1×	564 0.7×	550 0.9×	10	5.0k
Derek Wu	3.2k 1.5×	774 0.7×	1.2k 1.3×	394 0.5×	382 0.6×	18	5.1k
Anne L. Martel	1.9k 0.9×	978 0.8×	1.4k 1.5×	717 0.9×	481 0.8×	132	4.0k
Matthew P. Lungren	2.9k 1.4×	779 0.7×	2.3k 2.4×	669 0.8×	774 1.2×	96	6.1k
Varun Gulshan	3.2k 1.6×	1.5k 1.3×	1.4k 1.5×	361 0.4×	389 0.6×	9	5.8k

Countries citing papers authored by Ulaş Bağcı

Since Specialization

Citations

This map shows the geographic impact of Ulaş Bağcı'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 Ulaş Bağcı with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulaş Bağcı more than expected).

Fields of papers citing papers by Ulaş Bağcı

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ulaş Bağcı. 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 Ulaş Bağcı. The network helps show where Ulaş Bağcı may publish in the future.

Co-authorship network of co-authors of Ulaş Bağcı

This figure shows the co-authorship network connecting the top 25 collaborators of Ulaş Bağcı. A scholar is included among the top collaborators of Ulaş Bağcı 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 Ulaş Bağcı. Ulaş Bağcı 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

Gennaro, Nicolò, Amir A. Borhani, Linda C. Kelahan, et al.. (2025). Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer. Tomography. 11(3). 20–20.

Gao, Catherine A., Mary Carns, Kathleen Aren, et al.. (2025). Radiomic Features Detect Interstitial Lung Disease in Patients With Systemic Sclerosis. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A1707–A1707.

Keleş, Elif, Zheyuan Zhang, Linkai Peng, et al.. (2025). Pediatric pancreas segmentation from MRI scans with deep learning. Pancreatology. 25(5). 648–657. 1 indexed citations

Yılmaz, Ravza, et al.. (2025). Radiomics for Detecting Metaplastic Histology in Triple-Negative Breast Cancer: A Step Towards Personalized Therapy. Bioengineering. 12(9). 973–973.

Berhane, Haben, Gabriela Martinez, Tyler Jacobson, et al.. (2025). Anatomy-derived 3D Aortic Hemodynamics Using Fluid Physics–informed Deep Learning. Radiology. 315(2). e240714–e240714. 1 indexed citations

Jha, Debesh, Fiona R. Kolbinger, Ulaş Bağcı, et al.. (2024). THE BOSTON ERCP DATASET: A VIDEO DATASET FOR ADVANCED ENDOSCOPY. Gastrointestinal Endoscopy. 99(6). AB5–AB6.

Çiçek, Vedat & Ulaş Bağcı. (2024). AI-powered contrast-free cardiovascular magnetic resonance imaging for myocardial infarction. Frontiers in Cardiovascular Medicine. 11. 1457498–1457498. 1 indexed citations

Bağcı, Ulaş, et al.. (2024). Early stage lung cancer detection from speech sounds in natural environments. Biomedical Signal Processing and Control. 96. 106628–106628. 2 indexed citations

Jha, Debesh, Nikhil Kumar Tomar, Matthew Antalek, et al.. (2024). CT Liver Segmentation Via PVT-Based Encoding and Refined Decoding. 1–5. 12 indexed citations

10.

Jha, Debesh, Zheyuan Zhang, Elif Keleş, et al.. (2024). Explainable Transformer Prototypes for Medical Diagnoses. 1–5. 1 indexed citations

11.

Bozorgpour, Afshin, et al.. (2024). HCA-NET: Hierarchical Context Attention Network for Intervertebral Disc Semantic Labeling. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1–5. 1 indexed citations

12.

Çiçek, Vedat, Şahhan Kılıç, Selami Doğan, et al.. (2024). Predictive Value of Inflammatory Scores for Left Atrium Thrombosis in Ischemic Stroke Without Atrial Fibrillation. Medicina. 60(12). 2046–2046. 2 indexed citations

13.

Keleş, Elif, Zheyuan Zhang, Yury Velichko, et al.. (2024). Advances for Managing Pancreatic Cystic Lesions: Integrating Imaging and AI Innovations. Cancers. 16(24). 4268–4268. 4 indexed citations

14.

Çiçek, Vedat, et al.. (2024). A New Risk Prediction Model for the Assessment of Myocardial Injury in Elderly Patients Undergoing Non-Elective Surgery. Journal of Cardiovascular Development and Disease. 12(1). 6–6. 1 indexed citations

15.

Anwar, Syed Muhammad, et al.. (2023). Relational reasoning network for anatomical landmarking. Journal of Medical Imaging. 10(2). 24002–24002. 3 indexed citations

16.

Wintermark, Max, et al.. (2023). Current State of Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Traumatic Brain Injury Prognostication. Neuroimaging Clinics of North America. 33(2). 279–297. 6 indexed citations

17.

Keleş, Elif & Ulaş Bağcı. (2023). The past, current, and future of neonatal intensive care units with artificial intelligence: a systematic review. npj Digital Medicine. 6(1). 220–220. 30 indexed citations

18.

Dalmaz, Onat, et al.. (2023). COVID-19 Detection From Respiratory Sounds With Hierarchical Spectrogram Transformers. IEEE Journal of Biomedical and Health Informatics. 28(3). 1273–1284. 13 indexed citations

19.

Mansoor, Awais, Ulaş Bağcı, Ziyue Xu, et al.. (2014). A Generic Approach to Pathological Lung Segmentation. IEEE Transactions on Medical Imaging. 33(12). 2293–2310. 118 indexed citations

20.

Foster, Brent, Ulaş Bağcı, Awais Mansoor, Ziyue Xu, & Daniel J. Mollura. (2014). A review on segmentation of positron emission tomography images. Computers in Biology and Medicine. 50. 76–96. 259 indexed citations

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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