| Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network S Singh, D Gupta, RS Anand, V Kumar Biomedical Signal Processing and Control 18, 91-101, 2015 | 166 | 2015 |
| A hybrid edge-based segmentation approach for ultrasound medical images D Gupta, RS Anand Biomedical Signal Processing and Control 31, 116-126, 2017 | 99 | 2017 |
| Rheumatoid arthritis: atherosclerosis imaging and cardiovascular risk assessment using machine and deep learning–based tissue characterization NN Khanna, AD Jamthikar, D Gupta, M Piga, L Saba, C Carcassi, ... Current atherosclerosis reports 21, 1-14, 2019 | 96 | 2019 |
| A survey on coronary atherosclerotic plaque tissue characterization in intravascular optical coherence tomography A Boi, AD Jamthikar, L Saba, D Gupta, A Sharma, B Loi, JR Laird, ... Current atherosclerosis reports 20, 1-17, 2018 | 79 | 2018 |
| A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes A Jamthikar, D Gupta, NN Khanna, L Saba, T Araki, K Viskovic, HS Suri, ... Cardiovascular diagnosis and therapy 9 (5), 420, 2019 | 77 | 2019 |
| Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited? L Saba, A Jamthikar, D Gupta, NN Khanna, K Viskovic, HS Suri, A Gupta, ... International angiology 38 (6), 451-465, 2019 | 68 | 2019 |
| Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models A Jamthikar, D Gupta, L Saba, NN Khanna, T Araki, K Viskovic, ... Cardiovascular diagnosis and therapy 10 (4), 919, 2020 | 67 | 2020 |
| A hybrid segmentation method based on Gaussian kernel fuzzy clustering and region based active contour model for ultrasound medical images D Gupta, RS Anand, B Tyagi Biomedical Signal Processing and Control 16, 98-112, 2015 | 66 | 2015 |
| Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: A 500 … AD Jamthikar, D Gupta, LE Mantella, L Saba, JR Laird, AM Johri, JS Suri The International Journal of Cardiovascular Imaging 37, 1171-1187, 2021 | 64 | 2021 |
| Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound AD Jamthikar, D Gupta, L Saba, NN Khanna, K Viskovic, S Mavrogeni, ... Computers in biology and medicine 126, 104043, 2020 | 55 | 2020 |
| Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors A Jamthikar, D Gupta, NN Khanna, L Saba, JR Laird, JS Suri Indian heart journal 72 (4), 258-264, 2020 | 52 | 2020 |
| Nonlinear model for the carotid artery disease 10‐year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: a Japanese diabetes … NN Khanna, AD Jamthikar, T Araki, D Gupta, M Piga, L Saba, C Carcassi, ... Echocardiography 36 (2), 345-361, 2019 | 51 | 2019 |
| Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study NN Khanna, AD Jamthikar, D Gupta, A Nicolaides, T Araki, L Saba, ... Computers in biology and medicine 105, 125-143, 2019 | 51 | 2019 |
| A special report on changing trends in preventive stroke/cardiovascular risk assessment via B-mode ultrasonography A Jamthikar, D Gupta, NN Khanna, T Araki, L Saba, A Nicolaides, ... Cognitive Informatics, Computer Modelling, and Cognitive Science, 291-318, 2020 | 43 | 2020 |
| Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging AD Jamthikar, D Gupta, A Puvvula, AM Johri, NN Khanna, L Saba, ... Rheumatology international 40 (12), 1921-1939, 2020 | 42 | 2020 |
| Speckle filtering of ultrasound images using a modified non‐linear diffusion model in non‐subsampled shearlet domain D Gupta, RS Anand, B Tyagi IET Image Processing 9 (2), 107-117, 2015 | 42 | 2015 |
| Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1. 0 NN Khanna, AD Jamthikar, D Gupta, T Araki, M Piga, L Saba, C Carcassi, ... Medical & biological engineering & computing 57, 1553-1566, 2019 | 41 | 2019 |
| Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach E Cuadrado-Godia, AD Jamthikar, D Gupta, NN Khanna, T Araki, ... Computers in biology and medicine 108, 182-195, 2019 | 41 | 2019 |
| Nonsubsampled contourlet domain visible and infrared image fusion framework for fire detection using pulse coupled neural network and spatial fuzzy clustering SM Nemalidinne, D Gupta Fire Safety Journal 101, 84-101, 2018 | 39 | 2018 |
| Nonsubsampled shearlet domain fusion techniques for CT–MR neurological images using improved biological inspired neural model D Gupta Biocybernetics and Biomedical Engineering 38 (2), 262-274, 2018 | 38 | 2018 |
Ankush JamthikarRutgers Robert Wood Johnson Medical SchoolVerified email at students.vnit.ac.in
