Sarfaraz Hussein

880 total citations
12 papers, 458 citations indexed

About

Sarfaraz Hussein is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Sarfaraz Hussein has authored 12 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Sarfaraz Hussein's work include Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Pancreatic and Hepatic Oncology Research (2 papers). Sarfaraz Hussein is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Pancreatic and Hepatic Oncology Research (2 papers). Sarfaraz Hussein collaborates with scholars based in United States, Pakistan and Belgium. Sarfaraz Hussein's co-authors include Ulaş Bağcı, Candice W. Bolan, Pujan Kandel, Michael B. Wallace, Aliasghar Mortazi, Naji Khosravan, Jeremy R. Burt, Juan E. Corral, Waqas Sultani and Medhat Osman and has published in prestigious journals such as Gastroenterology, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Sarfaraz Hussein

12 papers receiving 435 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sarfaraz Hussein United States	7	248	206	102	79	64	12	458
Saima Rathore Pakistan	15	269 1.1×	247 1.2×	86 0.8×	210 2.7×	60 0.9×	27	559
Tahir Mahmood South Korea	13	342 1.4×	232 1.1×	60 0.6×	192 2.4×	61 1.0×	30	620
Vivek Kumar Singh United States	16	274 1.1×	356 1.7×	96 0.9×	225 2.8×	59 0.9×	45	688
Yanlin Tan China	17	224 0.9×	201 1.0×	31 0.3×	135 1.7×	99 1.5×	36	633
Clifford Yang United States	11	377 1.5×	356 1.7×	63 0.6×	87 1.1×	85 1.3×	22	673
Shuyue Guan United States	11	263 1.1×	261 1.3×	70 0.7×	232 2.9×	34 0.5×	27	556
Bibo Shi United States	10	159 0.6×	151 0.7×	30 0.3×	75 0.9×	80 1.3×	25	375
Norman Zerbe Germany	12	314 1.3×	501 2.4×	118 1.2×	194 2.5×	88 1.4×	34	780
Cristián Castillo-Olea Spain	8	174 0.7×	189 0.9×	42 0.4×	56 0.7×	24 0.4×	19	371
Dexing Kong China	14	381 1.5×	211 1.0×	24 0.2×	133 1.7×	49 0.8×	54	664

Countries citing papers authored by Sarfaraz Hussein

Since Specialization

Citations

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

Fields of papers citing papers by Sarfaraz Hussein

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarfaraz Hussein

This figure shows the co-authorship network connecting the top 25 collaborators of Sarfaraz Hussein. A scholar is included among the top collaborators of Sarfaraz Hussein 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 Sarfaraz Hussein. Sarfaraz Hussein is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Hussein, Sarfaraz, et al.. (2024). Joint Stream: Malignant Region Learning for Breast Cancer Diagnosis. Biomedical Signal Processing and Control. 99. 106899–106899. 2 indexed citations

Ali, Mohsen, et al.. (2022). Identifying out of distribution samples for skin cancer and malaria images. Biomedical Signal Processing and Control. 78. 103882–103882. 5 indexed citations

Hussein, Sarfaraz, et al.. (2021). Estimation of BMI from facial images using semantic segmentation based region-aware pooling. Computers in Biology and Medicine. 133. 104392–104392. 18 indexed citations

Hussein, Sarfaraz, Pujan Kandel, Candice W. Bolan, Michael B. Wallace, & Ulaş Bağcı. (2019). Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches. IEEE Transactions on Medical Imaging. 38(8). 1777–1787. 189 indexed citations

Echauz, Javier, et al.. (2019). Adversarial Campaign Mitigation via ROC-Centric Prognostics. Annual Conference of the PHM Society. 11(1). 1 indexed citations

Corral, Juan E., Sarfaraz Hussein, Pujan Kandel, et al.. (2019). Deep Learning to Classify Intraductal Papillary Mucinous Neoplasms Using Magnetic Resonance Imaging. Pancreas. 48(6). 805–810. 59 indexed citations

Hussein, Sarfaraz, Aydoğan Savran, Rita R. Kalyani, et al.. (2018). A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation. IEEE Transactions on Biomedical Engineering. 66(4). 1069–1081. 13 indexed citations

Burt, Jeremy R., et al.. (2018). Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks. British Journal of Radiology. 91(1089). 20170545–20170545. 120 indexed citations

Corral, Juan E., Sarfaraz Hussein, Pujan Kandel, et al.. (2018). Su1337 - Deep Learning to Diagnose Intraductal Papillary Mucinous Neoplasms (IPMN) with MRI. Gastroenterology. 154(6). S–524. 3 indexed citations

10.

Bağcı, Ulaş, et al.. (2017). Brown adipose tissue detected by PET/CT imaging is associated with less central obesity. Nuclear Medicine Communications. 38(7). 629–635. 25 indexed citations

11.

Xia, Yin, Sarfaraz Hussein, Vivek Kumar Singh, et al.. (2016). Context region discovery for automatic motion compensation in fluoroscopy. International Journal of Computer Assisted Radiology and Surgery. 11(6). 977–985. 3 indexed citations

12.

Hussein, Sarfaraz, Arjun Watane, David A. Reiter, et al.. (2016). Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans. IEEE Transactions on Medical Imaging. 36(3). 734–744. 20 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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