Purnendu Mishra
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View article: Development and Validation of Fully Automatic Deep Learning-Based Algorithms for Immunohistochemistry Reporting of Invasive Breast Ductal Carcinoma
Development and Validation of Fully Automatic Deep Learning-Based Algorithms for Immunohistochemistry Reporting of Invasive Breast Ductal Carcinoma Open
Immunohistochemistry (IHC) analysis is a well-accepted and widely used method for molecular subtyping, a procedure for prognosis and targeted therapy of breast carcinoma, the most common type of tumor affecting women. There are four molecu…
View article: Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentation
Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentation Open
Digital pathology and microscopy image analysis are widely employed in the segmentation of digitally scanned IHC slides, primarily to identify cancer and pinpoint regions of interest (ROI) indicative of tumor presence. However, current ROI…
View article: Multi-Stain Multi-Level Convolutional Network for Multi-Tissue breast cancer image segmentation
Multi-Stain Multi-Level Convolutional Network for Multi-Tissue breast cancer image segmentation Open
Digital pathology and microscopy image analysis are widely employed in the segmentation of digitally scanned IHC slides, primarily to identify cancer and pinpoint regions of interest (ROI) indicative of tumor presence. However, current ROI…
View article: Multiple-Hand 2D Pose Estimation From a Monocular RGB Image
Multiple-Hand 2D Pose Estimation From a Monocular RGB Image Open
Deep learning models and algorithms facilitate relatively easier ways of hand pose estimation from monocular RGB images compared to traditional approaches. Despite this, a majority of available algorithms use multiple-stage models to perfo…
View article: A novel approach for brain tissue segmentation and classification in infants' MRI images based on seeded region growing, foster corner detection theory, and sparse autoencoder
A novel approach for brain tissue segmentation and classification in infants' MRI images based on seeded region growing, foster corner detection theory, and sparse autoencoder Open
Brain tissue segmentation and classification in infant MRI images play a crucial role in early diagnosis of neurological disorders. In this paper, we propose a novel approach based on Seeded Region Growing, Foster Corner Detection Theory, …
View article: Anchors based method for fingertips position from a monocular RGB image using Deep Neural Network
Anchors based method for fingertips position from a monocular RGB image using Deep Neural Network Open
In Virtual, augmented, and mixed reality, the use of hand gestures is increasingly becoming popular to reduce the difference between the virtual and real world. The precise location of the fingertip is essential/crucial for a seamless expe…
View article: Anchors Based Method for Fingertips Position Estimation from a Monocular RGB Image using Deep Neural Network
Anchors Based Method for Fingertips Position Estimation from a Monocular RGB Image using Deep Neural Network Open
In Virtual, augmented, and mixed reality, the use of hand gestures is increasingly becoming popular to reduce the difference between the virtual and real world. The precise location of the fingertip is essential/crucial for a seamless expe…