| CT radiomics to predict high‐risk intraductal papillary mucinous neoplasms of the pancreas J Chakraborty, A Midya, L Gazit, M Attiyeh, L Langdon‐Embry, PJ Allen, ... Medical physics 45 (11), 5019-5029, 2018 | 116 | 2018 |
| Influence of CT acquisition and reconstruction parameters on radiomic feature reproducibility A Midya, J Chakraborty, M Gönen, RKG Do, AL Simpson Journal of Medical Imaging 5 (1), 011020-011020, 2018 | 114 | 2018 |
| Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation R Yamashita, T Perrin, J Chakraborty, JF Chou, N Horvat, MA Koszalka, ... European Radiology 30 (1), 195-205, 2020 | 71 | 2020 |
| Short-term reproducibility of radiomic features in liver parenchyma and liver malignancies on contrast-enhanced CT imaging T Perrin, A Midya, R Yamashita, J Chakraborty, T Saidon, WR Jarnagin, ... Abdominal Radiology 43 (12), 3271-3278, 2018 | 55 | 2018 |
| Computer-aided detection and diagnosis of mammographic masses using multi-resolution analysis of oriented tissue patterns J Chakraborty, A Midya, R Rabidas Expert Systems with Applications 99, 168-179, 2018 | 44 | 2018 |
| Neighborhood structural similarity mapping for the classification of masses in mammograms R Rabidas, A Midya, J Chakraborty IEEE journal of biomedical and health informatics 22 (3), 826-834, 2017 | 41 | 2017 |
| Classification of benign and malignant masses in mammograms using multi-resolution analysis of oriented patterns A Midya, J Chakraborty 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 411-414, 2015 | 31 | 2015 |
| A study of different texture features based on local operator for benign-malignant mass classification R Rabidas, A Midya, J Chakraborty, W Arif 6th International Conference On Advances In Computing & Communications, IN …, 2016 | 30 | 2016 |
| Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment S Khalighi, K Reddy, A Midya, KB Pandav, A Madabhushi, ... npj Precision Oncology 8 (1), 80, 2024 | 28 | 2024 |
| Moving object detection using modified temporal differencing and local fuzzy thresholding N Paul, A Singh, A Midya, PP Roy, DP Dogra The Journal of Supercomputing 73 (3), 1120-1139, 2017 | 25 | 2017 |
| Deep convolutional neural network for the classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma A Midya, J Chakraborty, LM Pak, J Zheng, WR Jarnagin, RKG Do, ... Medical Imaging 2018: Computer-Aided Diagnosis 10575, 501-506, 2018 | 24 | 2018 |
| Recurrence after resection of pancreatic cancer: can radiomics predict patients at greatest risk of liver metastasis? CP Zambirinis, A Midya, J Chakraborty, JF Chou, J Zheng, CA McIntyre, ... Annals of Surgical Oncology 29 (8), 4962-4974, 2022 | 23 | 2022 |
| Analysis of 2D singularities for mammographic mass classification R Rabidas, J Chakraborty, A Midya IET Computer Vision 11 (1), 22-32, 2017 | 20 | 2017 |
| 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 |
| Computerized diagnosis of liver tumors from CT scans using a deep neural network approach A Midya, J Chakraborty, R Srouji, RR Narayan, T Boerner, J Zheng, ... IEEE Journal of Biomedical and Health Informatics, 2023 | 18 | 2023 |
| 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 (3), 352-366, 2019 | 18 | 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 |
| Face detection using skin color modeling and geometric feature A Verma, S Achyut Raj, A Midya, J Chakraborty Informatics, Electronics & Vision (ICIEV), 2014 International Conference on, 1-6, 2014 | 15 | 2014 |
| Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases JM Creasy, A Midya, J Chakraborty, LB Adams, C Gomes, M Gonen, ... European Radiology 29 (1), 458-467, 2019 | 12 | 2019 |
Jayasree ChakrabortyHepatopancreatobiliary Service, Memorial Sloan Kettering Cancer CenterZweryfikowany adres z mskcc.org
