Abhishek Midya

1.0k total citations · 1 hit paper
37 papers, 683 citations indexed

About

Abhishek Midya is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Abhishek Midya has authored 37 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 16 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Artificial Intelligence. Recurrent topics in Abhishek Midya's work include Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (13 papers) and Image Retrieval and Classification Techniques (7 papers). Abhishek Midya is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (13 papers) and Image Retrieval and Classification Techniques (7 papers). Abhishek Midya collaborates with scholars based in United States, India and Canada. Abhishek Midya's co-authors include Jayasree Chakraborty, Amber L. Simpson, Richard Kinh Gian, Mithat Gönen, Peter J. Allen, Anant Madabhushi, Malak Abedalthagafi, Krunal Pandav, Sirvan Khalighi and William R. Jarnagin and has published in prestigious journals such as Annals of Surgery, Expert Systems with Applications and Medical Physics.

In The Last Decade

Abhishek Midya

35 papers receiving 667 citations

Hit Papers

align trajectories

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.

Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment

2024 95 citations Sirvan Khalighi, Abhishek Midya et al. npj Precision Oncology profile →

Peers

Abhishek Midya

RNMI

ONCOL

CVPR

PRM

Zeyan Xu China

Jan Hendrik Moltz Germany

Dmitry Goldgof United States

André Homeyer Germany

Jiawei Tian China

David Clunie United States

Jie Tian China

Jiawei Sun China

Jyoti Kini India

Zeyan Xu China

Abhishek Midya

440 ×1.0

RNMI

301 ×1.2

180 ×1.0

ONCOL

149 ×0.9

CVPR

91 ×0.8

PRM

Citations per year, relative to Abhishek Midya Abhishek Midya (= 1×) peers Zeyan Xu

Countries citing papers authored by Abhishek Midya

Since Specialization

Citations

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

Fields of papers citing papers by Abhishek Midya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhishek Midya

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

Gagnière, Johan, Abhishek Midya, Rikiya Yamashita, et al.. (2025). Postoperative Pancreatic Fistula After Pancreatoduodenectomy. Annals of Surgery.

Midya, Abhishek, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, et al.. (2025). Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men. JU Open Plus. 3(7).

Khalighi, Sirvan, et al.. (2024). Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment. npj Precision Oncology. 8(1). 80–80. 95 indexed citations breakdown →

Chakraborty, Jayasree, Abhishek Midya, Brenda F. Kurland, et al.. (2024). Use of Response Permutation to Measure an Imaging Dataset’s Susceptibility to Overfitting by Selected Standard Analysis Pipelines. Academic Radiology. 31(9). 3590–3596. 3 indexed citations

Midya, Abhishek, Vidya Sankar Viswanathan, Amr Mahran, et al.. (2023). Delta radiomic patterns on serial bi-parametric MRI are associated with pathologic upgrading in prostate cancer patients on active surveillance: preliminary findings. Frontiers in Oncology. 13. 1166047–1166047. 9 indexed citations

Zambirinis, Constantinos P., Abhishek Midya, Jayasree Chakraborty, et al.. (2022). Recurrence After Resection of Pancreatic Cancer: Can Radiomics Predict Patients at Greatest Risk of Liver Metastasis?. Annals of Surgical Oncology. 29(8). 4962–4974. 17 indexed citations

Midya, Abhishek, et al.. (2022). A multi features based background modeling approach for moving object detection. Optik. 260. 168980–168980. 5 indexed citations

Midya, Abhishek, et al.. (2020). Enhancement of Hazy Images Using Atmospheric Light Estimation Technique. Journal of Circuits Systems and Computers. 30(5). 2150078–2150078. 3 indexed citations

Yamashita, Rikiya, Jayasree Chakraborty, Joanne F. Chou, et al.. (2019). Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation. European Radiology. 30(1). 195–205. 55 indexed citations

10.

Creasy, John M., Abhishek Midya, Jayasree Chakraborty, et al.. (2018). Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases. European Radiology. 29(1). 458–467. 12 indexed citations

11.

Midya, Abhishek, Rikiya Yamashita, Jayasree Chakraborty, et al.. (2018). Short-term reproducibility of radiomic features in liver parenchyma and liver malignancies on contrast-enhanced CT imaging. Abdominal Radiology. 43(12). 3271–3278. 43 indexed citations

12.

Chakraborty, Jayasree, Linda M. Pak, Jian Zheng, et al.. (2018). Deep convolutional neural network for the classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. 79–79. 21 indexed citations

13.

Chakraborty, Jayasree, et al.. (2018). Computer-aided detection and diagnosis of mammographic masses using multi-resolution analysis of oriented tissue patterns. Expert Systems with Applications. 99. 168–179. 38 indexed citations

14.

Midya, Abhishek, Jayasree Chakraborty, Mithat Gönen, Richard Kinh Gian, & Amber L. Simpson. (2018). Influence of CT acquisition and reconstruction parameters on radiomic feature reproducibility. Journal of Medical Imaging. 5(1). 1–1. 82 indexed citations

15.

Chakraborty, Jayasree, et al.. (2016). Analysis of 2D singularities for mammographic mass classification. IET Computer Vision. 11(1). 22–32. 13 indexed citations

16.

Midya, Abhishek, et al.. (2016). Benign-malignant mass classification in mammogram using edge weighted local texture features. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9785. 97851X–97851X. 10 indexed citations

17.

Midya, Abhishek, et al.. (2014). Face detection using skin color modeling and geometric feature. 4642. 1–6. 6 indexed citations

18.

Chakraborti, Tathagata, Abhronil Sengupta, Abhishek Midya, Amit Konar, & Somnath Sengupta. (2013). 3-D model assisted facial error concealment technique using regenerative particle filter based tracking. 20. 1–6. 1 indexed citations

19.

Midya, Abhishek, Rajeev Ranjan, & Somnath Sengupta. (2013). Scene content driven FEC allocation for video streaming. Signal Processing Image Communication. 29(1). 37–48. 4 indexed citations

20.

Midya, Abhishek & Somnath Sengupta. (2012). Scene transition based adaptive GOP selection for increasing coding efficiency & resiliency. 770–773. 3 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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