D
Deep Gupta
Researcher at Visvesvaraya National Institute of Technology
Publications - 59
Citations - 1200
Deep Gupta is an academic researcher from Visvesvaraya National Institute of Technology. The author has contributed to research in topics: Image fusion & Framingham Risk Score. The author has an hindex of 19, co-authored 50 publications receiving 789 citations. Previous affiliations of Deep Gupta include Indian Institute of Technology Roorkee.
Papers
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Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network
TL;DR: Experimental results demonstrate that the proposed method does not only produce better results by successfully fusing the different CT and MR images, but also ensures an improvement in the various quantitative parameters as compared to other existing methods.
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A hybrid edge-based segmentation approach for ultrasound medical images
Deep Gupta,R. S. Anand +1 more
TL;DR: A hybrid approach for accurate segmentation of the ultrasound medical images is presented that utilizes both the features of kernel fuzzy clustering with spatial constraints and edge based active contour method using distance regularized level set (DRLS) function.
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Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization
Narendra N. Khanna,Ankush D Jamthikar,Deep Gupta,Matteo Piga,Luca Saba,Carlo Carcassi,Argiris A. Giannopoulos,Andrew N. Nicolaides,Andrew N. Nicolaides,John R. Laird,Harman S. Suri,Sophie Mavrogeni,A.D. Protogerou,Petros P. Sfikakis,George D. Kitas,George D. Kitas,Jasjit S. Suri +16 more
TL;DR: Intelligence-based paradigms are useful for accurate tissue characterization and risk stratification of RA patients and inflammation is a common link between RA and atherosclerotic plaque buildup, which could facilitate cardiovascular risk assessment in RA patients.
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A survey on coronary atherosclerotic plaque tissue characterization in intravascular optical coherence tomography
Alberto Boi,Ankush D Jamthikar,Luca Saba,Deep Gupta,Aditya Sharma,Bruno Loi,John R. Laird,Narendra N. Khanna,Jasjit S. Suri +8 more
TL;DR: A detailed comparison among various methodologies utilized for plaque tissue characterization, classification, and arterial measurements in OCT is presented, finding a combination of machine learning and deep learning techniques is a best possible solution that provides improved OCT-based risk stratification.
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Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models.
Ankush D Jamthikar,Deep Gupta,Luca Saba,Narendra N. Khanna,Tadashi Araki,Klaudija Višković,Sophie Mavrogeni,John R. Laird,Gyan Pareek,Martin Miner,Petros P. Sfikakis,Athanasios Protogerou,Vijay Viswanathan,Aditya Sharma,Andrew Nicolaides,George D. Kitas,Jasjit S. Suri +16 more
TL;DR: ML-based CVD/stroke risk calculator provided a higher predictive ability of 10-year CVD or stroke events compared to the 13 different types of statistically derived risk calculators including integrated model AECRS 2.0.