| Lung nodule detection from feature engineering to deep learning in thoracic CT images: a comprehensive review A Halder, D Dey, AK Sadhu Journal of digital imaging 33 (3), 655-677, 2020 | 89 | 2020 |
| Delineation and diagnosis of brain tumors from post contrast T1-weighted MR images using rough granular computing and random forest S Koley, AK Sadhu, P Mitra, B Chakraborty, C Chakraborty Applied Soft Computing 41, 453-465, 2016 | 46 | 2016 |
| Deep learning for screening of interstitial lung disease patterns in high-resolution CT images S Agarwala, M Kale, D Kumar, R Swaroop, A Kumar, AK Dhara, ... Clinical radiology 75 (6), 481. e1-481. e8, 2020 | 33 | 2020 |
| A heuristic approach to automated nipple detection in digital mammograms M Jas, S Mukhopadhyay, J Chakraborty, A Sadhu, N Khandelwal Journal of digital imaging 26, 932-940, 2013 | 27 | 2013 |
| Computer-assisted delineation of hematoma from CT volume using autoencoder and Chan Vese model MK Nag, S Chatterjee, AK Sadhu, J Chatterjee, N Ghosh International journal of computer assisted radiology and surgery 14, 259-269, 2019 | 25 | 2019 |
| Mammogram segmentation using multi-atlas deformable registration MK Sharma, M Jas, V Karale, A Sadhu, S Mukhopadhyay Computers in biology and medicine 110, 244-253, 2019 | 23 | 2019 |
| Infratemporal fossa myoepithelial carcinoma—a rare case report A Ghosh, S Saha, VP Saha, A Sadhu, S Chattopadhyay Oral and maxillofacial surgery 13, 59-62, 2009 | 22 | 2009 |
| Automatic characterization of masses in mammograms J Chakraborty, A Midya, S Mukhopadhyay, A Sadhu 2013 6th International Conference on Biomedical Engineering and Informatics …, 2013 | 20 | 2013 |
| Computer-aided detection of mammographic masses using hybrid region growing controlled by multilevel thresholding J Chakraborty, A Midya, S Mukhopadhyay, RM Rangayyan, A Sadhu, ... Journal of Medical and Biological Engineering 39, 352-366, 2019 | 17 | 2019 |
| Benign-malignant mass classification in mammogram using edge weighted local texture features R Rabidas, A Midya, A Sadhu, J Chakraborty Medical Imaging 2016: Computer-Aided Diagnosis 9785, 491-496, 2016 | 15 | 2016 |
| Detection of the nipple in mammograms with Gabor filters and the Radon transform J Chakraborty, A Midya, S Mukhopadhyay, RM Rangayyan, A Sadhu, ... Biomedical Signal Processing and Control 15, 80-89, 2015 | 15 | 2015 |
| Adaptive local ternary pattern on parameter optimized-faster region convolutional neural network for pulmonary emphysema diagnosis S Mondal, AK Sadhu, PK Dutta IEEE Access 9, 114135-114152, 2021 | 13 | 2021 |
| A quantitative lung computed tomography image feature for multi-center severity assessment of COVID-19 B Ghosh, N Kumar, N Singh, AK Sadhu, N Ghosh, P Mitra, J Chatterjee MedRxiv, 2020.07. 13.20152231, 2020 | 12 | 2020 |
| Automated in vivo delineation of lumen wall using intravascular ultrasound imaging D China, MK Nag, KM Mandana, AK Sadhu, P Mitra, C Chakraborty 2016 38th Annual international conference of the IEEE engineering in …, 2016 | 11 | 2016 |
| Multispectral MRI image fusion for enhanced visualization of meningioma brain tumors and edema using contourlet transform and fuzzy statistics S Koley, A Galande, B Kelkar, AK Sadhu, D Sarkar, C Chakraborty Journal of Medical and Biological Engineering 36, 470-484, 2016 | 11 | 2016 |
| Edge weighted local texture features for the categorization of mammographic masses A Midya, R Rabidas, A Sadhu, J Chakraborty Journal of Medical and Biological Engineering 38, 457-468, 2018 | 10 | 2018 |
| An association study of severity of intellectual disability with peripheral biomarkers of disabled children in a rehabilitation home, Kolkata, India A Sengupta, U Das, K Manna, S Biswas, S Datta, A Khan, T Bhattacharya, ... Scientific reports 9 (1), 13652, 2019 | 9 | 2019 |
| A computer vision approach for lung cancer classification using FNAC-based cytological images M Dholey, A Sarkar, M Maity, A Giri, A Sadhu, K Chaudhury, S Das, ... Proceedings of 2nd International Conference on Computer Vision & Image …, 2018 | 9 | 2018 |
| Segmentation of lung field in HRCT images using U-net based fully convolutional networks A Kumar, S Agarwala, AK Dhara, D Nandi, SB Thakur, AK Bhadra, ... Medical Image Understanding and Analysis: 22nd Conference, MIUA 2018 …, 2018 | 8 | 2018 |
| Quantitative analysis of brain herniation from non-contrast CT images using deep learning MK Nag, A Gupta, AS Hariharasudhan, AK Sadhu, A Das, N Ghosh Journal of Neuroscience Methods 349, 109033, 2021 | 7 | 2021 |
Jayasree ChakrabortyHepatopancreatobiliary Service, Memorial Sloan Kettering Cancer CenterVerified email at mskcc.org
