Search Results for author: Sharath M. Shankaranarayana

Found 12 papers, 4 papers with code

Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation

1 code implementation14 Aug 2019 Balamurali Murugesan, Kaushik Sarveswaran, Sharath M. Shankaranarayana, Keerthi Ram, Jayaraj Joseph, Mohanasankar Sivaprakasam

For the task of medical image segmentation, fully convolutional network (FCN) based architectures have been extensively used with various modifications.

Image Segmentation Medical Image Segmentation +2

Constrained Monotonic Neural Networks

2 code implementations24 May 2022 Davor Runje, Sharath M. Shankaranarayana

Wider adoption of neural networks in many critical domains such as finance and healthcare is being hindered by the need to explain their predictions and to impose additional constraints on them.

A context based deep learning approach for unbalanced medical image segmentation

1 code implementation8 Jan 2020 Balamurali Murugesan, Kaushik Sarveswaran, Vijaya Raghavan S, Sharath M. Shankaranarayana, Keerthi Ram, Mohanasankar Sivaprakasam

Foreground-background class imbalance is a common occurrence in medical images, and U-Net has difficulty in handling class imbalance because of its cross entropy (CE) objective function.

Image Segmentation Medical Image Segmentation +2

Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation

no code implementations4 Feb 2019 Sharath M. Shankaranarayana, Keerthi Ram, Kaushik Mitra, Mohanasankar Sivaprakasam

Glaucoma is a serious ocular disorder for which the screening and diagnosis are carried out by the examination of the optic nerve head (ONH).

Depth Estimation

RespNet: A deep learning model for extraction of respiration from photoplethysmogram

no code implementations12 Feb 2019 Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan, Sharath M. Shankaranarayana, Keerthi Ram, Preejith S. P, Jayaraj Joseph, Mohanasankar Sivaprakasam

Recently, due to the widespread adoption of wearable smartwatches with in-built Photoplethysmogram (PPG) sensor, it is being considered as a viable candidate for continuous and unobtrusive respiration monitoring.

ALIME: Autoencoder Based Approach for Local Interpretability

no code implementations4 Sep 2019 Sharath M. Shankaranarayana, Davor Runje

Inthis work, we propose a locally interpretable method, which is inspiredby one of the recent tools that has gained a lot of interest, called localinterpretable model-agnostic explanations (LIME).

Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks

no code implementations15 Jul 2020 Sharath M. Shankaranarayana, Keerthi Ram, Kaushik Mitra, Mohanasankar Sivaprakasam

One of the important parameters for the assessment of glaucoma is optic nerve head (ONH) evaluation, which usually involves depth estimation and subsequent optic disc and cup boundary extraction.

Depth Estimation

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