Ajay Basavanhally

3.2k total citations · 2 hit papers
28 papers, 2.3k citations indexed

About

Ajay Basavanhally is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ajay Basavanhally has authored 28 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 13 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ajay Basavanhally's work include AI in cancer detection (25 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Digital Imaging for Blood Diseases (7 papers). Ajay Basavanhally is often cited by papers focused on AI in cancer detection (25 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Digital Imaging for Blood Diseases (7 papers). Ajay Basavanhally collaborates with scholars based in United States and Colombia. Ajay Basavanhally's co-authors include Anant Madabhushi, Shridar Ganesan, Michael D. Feldman, John Tomaszewski, Natalie Shih, Ángel Cruz-Roa, Fabio A. González, Hannah Gilmore, Gyan Bhanot and Andrew Janowczyk and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Ajay Basavanhally

28 papers receiving 2.2k citations

Hit Papers

Automatic detection of invasive ductal carcinoma in whole... 2014 2026 2018 2022 2014 2017 100 200 300
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.

  1. Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks
    2014 377 citations Ángel Cruz-Roa, Ajay Basavanhally et al. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE profile →
  2. Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent
    2017 349 citations Ángel Cruz-Roa, Hannah Gilmore et al. Scientific Reports profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ajay Basavanhally United States 19 1.8k 1.1k 1.0k 395 273 28 2.3k
Fuyong Xing United States 28 1.7k 0.9× 944 0.8× 1.4k 1.3× 681 1.7× 274 1.0× 79 2.9k
Korsuk Sirinukunwattana United Kingdom 16 1.6k 0.9× 1.1k 0.9× 969 0.9× 341 0.9× 165 0.6× 38 2.2k
Shan E Ahmed Raza United Kingdom 19 1.3k 0.7× 884 0.8× 727 0.7× 355 0.9× 170 0.6× 55 2.1k
Laura E. Boucheron United States 12 1.2k 0.7× 552 0.5× 844 0.8× 386 1.0× 174 0.6× 40 1.8k
Ángel Cruz-Roa Colombia 13 1.4k 0.7× 852 0.7× 776 0.8× 206 0.5× 133 0.5× 40 1.8k
Humayun Irshad United States 13 999 0.5× 499 0.4× 728 0.7× 437 1.1× 196 0.7× 20 1.5k
Meyke Hermsen Netherlands 13 1.1k 0.6× 734 0.6× 428 0.4× 198 0.5× 146 0.5× 22 1.6k
António Polónia Portugal 18 977 0.5× 809 0.7× 361 0.4× 155 0.4× 397 1.5× 49 1.7k
Allen P. Miraflor United States 7 1.3k 0.7× 944 0.8× 446 0.4× 200 0.5× 180 0.7× 11 1.8k
Abhishek Vahadane India 8 1.0k 0.5× 590 0.5× 708 0.7× 276 0.7× 70 0.3× 10 1.3k

Countries citing papers authored by Ajay Basavanhally

Since Specialization
Citations

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

Fields of papers citing papers by Ajay Basavanhally

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ajay Basavanhally

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

All Works

20 of 20 papers shown
1.
McNamara, George, Justin Lucas, John F. Beeler, et al.. (2020). New Technologies to Image Tumors. Cancer treatment and research. 180. 51–94. 4 indexed citations
2.
Mohammadi, Amir H., Lori J. Goldstein, Hannah Gilmore, et al.. (2018). Image-based risk score to predict recurrence of ER+ breast cancer in ECOG-ACRIN Cancer Research Group E2197.. Journal of Clinical Oncology. 36(15_suppl). 540–540. 8 indexed citations
3.
Cruz-Roa, Ángel, Hannah Gilmore, Ajay Basavanhally, et al.. (2018). High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection. PLoS ONE. 13(5). e0196828–e0196828. 95 indexed citations
4.
Cruz-Roa, Ángel, Hannah Gilmore, Ajay Basavanhally, et al.. (2017). Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent. Scientific Reports. 7(1). 46450–46450. 349 indexed citations breakdown →
5.
Janowczyk, Andrew, Ajay Basavanhally, & Anant Madabhushi. (2016). Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology. Computerized Medical Imaging and Graphics. 57. 50–61. 151 indexed citations
6.
Basavanhally, Ajay, Satish E. Viswanath, & Anant Madabhushi. (2015). Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer. PLoS ONE. 10(5). e0117900–e0117900. 9 indexed citations
7.
Cruz-Roa, Ángel, John Arévalo, Ajay Basavanhally, Anant Madabhushi, & Fabio A. González. (2015). A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9287. 92870G–92870G. 9 indexed citations
8.
Wang, Haibo, Ángel Cruz-Roa, Ajay Basavanhally, et al.. (2014). Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features. Journal of Medical Imaging. 1(3). 34003–34003. 249 indexed citations
9.
Ali, Sahirzeeshan, et al.. (2013). Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology. Lecture notes in computer science. 16(Pt 2). 238–245. 5 indexed citations
10.
Basavanhally, Ajay, Shridar Ganesan, Michael D. Feldman, et al.. (2013). Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides. IEEE Transactions on Biomedical Engineering. 60(8). 2089–2099. 101 indexed citations
11.
Basavanhally, Ajay & Anant Madabhushi. (2013). EM-based segmentation-driven color standardization of digitized histopathology. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8676. 86760G–86760G. 40 indexed citations
12.
Basavanhally, Ajay, Michael D. Feldman, Natalie Shih, et al.. (2012). Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX. Journal of Pathology Informatics. 2(2). 1–1. 45 indexed citations
13.
Basavanhally, Ajay, Elaine Yu, Jun Xu, et al.. (2011). Incorporating domain knowledge for tubule detection in breast histopathology using O'Callaghan neighborhoods. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7963. 796310–796310. 52 indexed citations
14.
Madabhushi, Anant, Shannon C. Agner, Ajay Basavanhally, Scott Doyle, & George Lee. (2011). Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. Computerized Medical Imaging and Graphics. 35(7-8). 506–514. 94 indexed citations
15.
Fatakdawala, Hussain, Jun Xu, Ajay Basavanhally, et al.. (2010). Expectation–Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology. IEEE Transactions on Biomedical Engineering. 57(7). 1676–1689. 160 indexed citations
16.
Madabhushi, Anant, Ajay Basavanhally, Scott Doyle, Shannon C. Agner, & George Lee. (2010). Computer-aided prognosis: Predicting patient and disease outcome via multi-modal image analysis. 8. 1415–1418. 8 indexed citations
17.
Basavanhally, Ajay, Shridar Ganesan, Shannon C. Agner, et al.. (2009). Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology. IEEE Transactions on Biomedical Engineering. 57(3). 642–653. 207 indexed citations
18.
Madabhushi, Anant, Ajay Basavanhally, Jun Xu, et al.. (2009). Computerized Histologic Image-Based Risk Score (IbRiS) Classifier for ER+ Breast Cancer.. Cancer Research. 69(24_Supplement). 3046–3046. 4 indexed citations
19.
Alexe, Gabriela, James Monaco, Scott Doyle, et al.. (2009). Towards Improved Cancer Diagnosis and Prognosis Using Analysis of Gene Expression Data and Computer Aided Imaging. Experimental Biology and Medicine. 234(8). 860–879. 32 indexed citations
20.
Jenkins, Michael W., et al.. (2007). In vivo gated 4D imaging of the embryonic heart using optical coherence tomography. Journal of Biomedical Optics. 12(3). 30505–30505. 76 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Fuyong Xing Breakdown of academic impact, for papers by Korsuk Sirinukunwattana Breakdown of academic impact, for papers by Shan E Ahmed Raza Breakdown of academic impact, for papers by Laura E. Boucheron Breakdown of academic impact, for papers by Ángel Cruz-Roa Breakdown of academic impact, for papers by Humayun Irshad Breakdown of academic impact, for papers by Meyke Hermsen Breakdown of academic impact, for papers by António Polónia Breakdown of academic impact, for papers by Allen P. Miraflor Breakdown of academic impact, for papers by Abhishek Vahadane
Rankless by CCL
2026