
Rishabh SharmaNarsee Monjee Institute of Management Studies
Rishabh Sharma
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10
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Publications (10)
Adversarial training has attracted much attention in enhancing the visual realism of images, but its efficacy in clinical imaging has not yet been explored. This work investigated adversarial training in a clinical context, by training 206 networks on the OASIS-1 dataset for improving low-resolution and low signal-to-noise ratio (SNR) magnetic reso...
This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and undersampled MRI in various acquisition protocols. The objective is to determine the validity of differences between different DUNet configurations and their impact on image quality metrics...
MR scans of low-gamma X-nuclei, low-concentration metabolites, or standard imaging at very low field entail a challenging tradeoff between resolution, signal-to-noise, and acquisition duration. Deep learning (DL) techniques, such as UNets, can potentially be used to improve such “low-quality” (LQ) images. We investigate three UNets for upscaling LQ...
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed 10 minutes after injection of the contrast agent, provides high contrast between viable and nonviable myocardi...
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed several minutes after injection of the contrast agent, provides high contrast between viable and nonviable myo...
This work introduces a novel Stacked Multimodal (SM2N2) architecture and assess its performance in classifying whether a patient have or not Myocardial Infarction. Central to this SM2N2 architecture is the use of images and clinical data as input. Comparison studies of Multimodal Neural Network (M2N2) component of SM2N2 with AlexNet3D model demonst...
A multitude of dietary factors from dietary fat to macro and micronutrients intakes have been associated with breast cancer, yet data are still equivocal. Therefore, utilizing data from the large, multi-year, cross-sectional National Health and Nutrition Examination Survey (NHANES), we applied a novel, modern statistical shrinkage technique, logist...