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Your search keyword '"Sanil Garg"' showing total 3 results
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3 results on '"Sanil Garg"'

1. Deep Learning for Detecting and Subtyping Renal Cell Carcinoma on Contrast-Enhanced CT Scans Using 2D Neural Network with Feature Consistency Techniques

Author

Amit Gupta, Rohan Raju Dhanakshirur, Kshitiz Jain, Sanil Garg, Neel Yadav, Amlesh Seth, and Chandan J. Das

Subjects
renal cell carcinoma, deep learning, classification, detection, F1 score, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Objective The aim of this study was to explore an innovative approach for developing deep learning (DL) algorithm for renal cell carcinoma (RCC) detection and subtyping on computed tomography (CT): clear cell RCC (ccRCC) versus non-ccRCC using two-dimensional (2D) neural network architecture and feature consistency modules.

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2. Predicting Renal Cell Carcinoma Subtypes and Fuhrman Grading Using Multiphasic CT-Based Texture Analysis and Machine Learning Techniques

Author

Amit Gupta, Sanil Garg, Neel Yadav, Rohan Raju Dhanakshirur, Kshitiz Jain, Rishi Nayyar, Seema Kaushal, and Chandan J. Das

Subjects
texture analysis, machine learning, renal cell carcinoma, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Objectives The aim of this study is to evaluate computed tomography texture analysis (CTTA) on multiphase CT scans for distinguishing clear cell renal cell carcinoma (ccRCC) from non-ccRCC and predicting Fuhrman's grade in ccRCC using open-source Python libraries.

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