| Contrast enhancement and brightness preserving of digital mammograms using fuzzy clipped contrast-limited adaptive histogram equalization algorithm S Jenifer, S Parasuraman, A Kadirvelu Applied Soft Computing 42, 167-177, 2016 | 128 | 2016 |
| Deep learning for predicting enhancing lesions in multiple sclerosis from noncontrast MRI PA Narayana, I Coronado, SJ Sujit, JS Wolinsky, FD Lublin, RE Gabr Radiology 294 (2), 398-404, 2020 | 79 | 2020 |
| Brain and lesion segmentation in multiple sclerosis using fully convolutional neural networks: A large-scale study RE Gabr, I Coronado, M Robinson, SJ Sujit, S Datta, X Sun, WJ Allen, ... Multiple Sclerosis Journal 26 (10), 1217-1226, 2020 | 77 | 2020 |
| Automated image quality evaluation of structural brain MRI using an ensemble of deep learning networks SJ Sujit, I Coronado, A Kamali, PA Narayana, RE Gabr Journal of Magnetic Resonance Imaging 50 (4), 1260-1267, 2019 | 67 | 2019 |
| Deep‐learning‐based neural tissue segmentation of MRI in multiple sclerosis: effect of training set size PA Narayana, I Coronado, SJ Sujit, JS Wolinsky, FD Lublin, RE Gabr Journal of Magnetic Resonance Imaging 51 (5), 1487-1496, 2020 | 37 | 2020 |
| Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning PA Narayana, I Coronado, SJ Sujit, X Sun, JS Wolinsky, RE Gabr Magnetic resonance imaging 65, 8-14, 2020 | 24 | 2020 |
| Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study MB Saad, L Hong, M Aminu, NI Vokes, P Chen, M Salehjahromi, K Qin, ... The Lancet Digital Health 5 (7), e404-e420, 2023 | 18 | 2023 |
| Automated image quality evaluation of structural brain magnetic resonance images using deep convolutional neural networks SJ Sujit, RE Gabr, I Coronado, M Robinson, S Datta, PA Narayana 2018 9th Cairo International Biomedical Engineering Conference (CIBEC), 33-36, 2018 | 17 | 2018 |
| An efficient biomedical imaging technique for automatic detection of abnormalities in digital mammograms S Jenifer, S Parasuraman, A Kadirvel Journal of Medical Imaging and Health Informatics 4 (2), 291-296, 2014 | 12 | 2014 |
| Multimodal MRI segmentation of brain tissue and T2-hyperintense white matter lesions in multiple sclerosis using deep convolutional neural networks and a large multi-center … PA Narayana, I Coronado, M Robinson, SJ Sujit, S Datta, X Sun, ... 2018 9th Cairo International Biomedical Engineering Conference (CIBEC), 13-16, 2018 | 11 | 2018 |
| Circulating tumor DNA and radiological tumor volume identify patients at risk for relapse with resected, early-stage non-small-cell lung cancer HT Tran, S Heeke, S Sujit, N Vokes, J Zhang, M Aminu, VK Lam, ... Annals of Oncology 35 (2), 183-189, 2024 | 8 | 2024 |
| Deep learning enabled brain shunt valve identification using mobile phones SJ Sujit, E Bonfante, A Aein, I Coronado, R Riascos-Castaneda, ... Computer methods and programs in biomedicine 210, 106356, 2021 | 7 | 2021 |
| Habitat imaging biomarkers for diagnosis and prognosis in cancer patients infected with COVID-19 M Aminu, D Yadav, L Hong, E Young, P Edelkamp Jr, M Saad, ... Cancers 15 (1), 275, 2022 | 4 | 2022 |
| Otsu's method for clip limiting histograms for contrast enhancement of digital mammograms S Jenifer, S Parasuraman, A Kadirvelu 2014 IEEE International Conference on Computational Intelligence and …, 2014 | 3 | 2014 |
| Automated Cellular-Level Dual Global Fusion of Whole-Slide Imaging for Lung Adenocarcinoma Prognosis S Diao, P Chen, E Showkatian, R Bandyopadhyay, FR Rojas, B Zhu, ... Cancers 15 (19), 4824, 2023 | 2 | 2023 |
| Fuzzy clustering in digital mammograms using Gray Level co-occurrence matrices SJ Sujit, S Parasuraman, A Kadirvelu 2012 International Conference on Emerging Trends in Electrical Engineering …, 2012 | 2 | 2012 |
| Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept M Salehjahromi, TV Karpinets, SJ Sujit, M Qayati, P Chen, M Aminu, ... Cell Reports Medicine 5 (3), 2024 | 1 | 2024 |
| Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights SJ Sujit, M Aminu, TV Karpinets, P Chen, MB Saad, M Salehjahromi, ... Nature Communications 15 (1), 3152, 2024 | | 2024 |
| Pathomics reveals the molecular and immune evolution from lung preneoplasia to invasive adenocarcinoma P Chen, F Rojas, X Hu, J Fujimoto, A Serrano, B Zhu, L Hong, ... Cancer Research 83 (7_Supplement), 5443-5443, 2023 | | 2023 |
| Combining Habitat Analysis and Autoencoder Neural Network for Feature Extraction to Predict COVID 19 Infection in CT Images TT Huynh, SJ Sujit PhD, M Saad PhD, KK Brock PhD, CC Wu MD, ... The University of Texas MD Anderson Cancer Center, 2021 | | 2021 |
Ivan CoronadoUniversity of Texas Health Science CenterZweryfikowany adres z uth.tmc.edu
