Search Results for author: Dwarikanath Mahapatra

Found 26 papers, 2 papers with code

CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis

no code implementations15 Jun 2021 Dwarikanath Mahapatra, Ankur Singh

While medical image segmentation is an important task for computer aided diagnosis, the high expertise requirement for pixelwise manual annotations makes it a challenging and time consuming task.

Data Augmentation Image Generation +3

Gated Fusion Network for SAO Filter and Inter Frame Prediction in Versatile Video Coding

no code implementations25 May 2021 Shiba Kuanar, Dwarikanath Mahapatra, Vassilis Athitsos, K. R Rao

To achieve higher coding efficiency, Versatile Video Coding (VVC) includes several novel components, but at the expense of increasing decoder computational complexity.


Multi-scale Deep Learning Architecture for Nucleus Detection in Renal Cell Carcinoma Microscopy Image

no code implementations28 Apr 2021 Shiba Kuanar, Vassilis Athitsos, Dwarikanath Mahapatra, Anand Rajan

Clear cell renal cell carcinoma (ccRCC) is one of the most common forms of intratumoral heterogeneity in the study of renal cancer.

Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition

no code implementations22 Apr 2021 Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, ZongYuan Ge

For example, there are estimated more than 40 different kinds of retinal diseases with variable morbidity, however with more than 30+ conditions are very rare from the global patient cohorts, which results in a typical long-tailed learning problem for deep learning-based screening models.

Knowledge Distillation

Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation

no code implementations13 Apr 2021 Dwarikanath Mahapatra

We demonstrate the benefits of the proposed approach, termed Interpretability-Driven Sample Selection (IDEAL), in an active learning setup aimed at lung disease classification and histopathology image segmentation.

Active Learning General Classification +3

Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation

no code implementations28 Feb 2021 Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Mehrtash Harandi, Tom Drummond, Tongliang Liu, ZongYuan Ge

In this paper, we systematically discuss and define the two common types of label noise in medical images - disagreement label noise from inconsistency expert opinions and single-target label noise from wrong diagnosis record.

General Classification Image Classification +1

Anomaly Detection on X-Rays Using Self-Supervised Aggregation Learning

no code implementations19 Oct 2020 Behzad Bozorgtabar, Dwarikanath Mahapatra, Guillaume Vray, Jean-Philippe Thiran

Deep anomaly detection models using a supervised mode of learning usually work under a closed set assumption and suffer from overfitting to previously seen rare anomalies at training, which hinders their applicability in a real scenario.

Anomaly Detection

Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance

no code implementations5 Aug 2020 Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran, Ling Shao

Although generative adversarial network (GAN) based style transfer is state of the art in histopathology color-stain normalization, they do not explicitly integrate structural information of tissues.

Style Transfer

Registration of Histopathogy Images Using Structural Information From Fine Grained Feature Maps

no code implementations4 Jul 2020 Dwarikanath Mahapatra

Registration is an important part of many clinical workflows and factually, including information of structures of interest improves registration performance.

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

no code implementations CVPR 2020 Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran, Ling Shao

The proposed method outperforms state-of-the-art segmentation methods on the public RETOUCH dataset having images captured from different acquisition procedures.

Data Augmentation Image Generation +2

Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning

no code implementations24 Mar 2020 Lie Ju, Xin Wang, Xin Zhao, Huimin Lu, Dwarikanath Mahapatra, Paul Bonnington, ZongYuan Ge

In addition, we conduct additional experiments to show the effectiveness of SALL from the aspects of reliability and interpretability in the context of medical imaging application.

General Classification Image Classification +2

Generative Adversarial Networks And Domain Adaptation For Training Data Independent Image Registration

no code implementations18 Oct 2019 Dwarikanath Mahapatra

This is achieved by unsupervised domain adaptation in the registration process and allows for easier application to different datasets without extensive retraining. To achieve our objective we train a network that transforms the given input image pair to a latent feature space vector using autoencoders.

Image Registration Medical Image Registration +1

Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation

1 code implementation11 Oct 2019 Yunyan Xing, ZongYuan Ge, Rui Zeng, Dwarikanath Mahapatra, Jarrel Seah, Meng Law, Tom Drummond

We demonstrate the effectiveness of our model on two tasks: (i) we invite certified radiologists to assess the quality of the generated synthetic images against real and other state-of-the-art generative models, and (ii) data augmentation to improve the performance of disease localisation.

Data Augmentation Image-to-Image Translation

sZoom: A Framework for Automatic Zoom into High Resolution Surveillance Videos

no code implementations23 Sep 2019 Mukesh Saini, Benjamin Guthier, Hao Kuang, Dwarikanath Mahapatra, Abdulmotaleb El Saddik

While viewing on a mobile device, a user can manually zoom into this high resolution video to get more detailed view of objects and activities.

AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering

no code implementations6 Jul 2019 Dwarikanath Mahapatra

We propose a method to predict severity of age related macular degeneration (AMD) from input optical coherence tomography (OCT) images.

Image Registration severity prediction

Progressive Generative Adversarial Networks for Medical Image Super resolution

no code implementations6 Feb 2019 Dwarikanath Mahapatra, Behzad Bozorgtabar

Our primary contribution is in proposing a multistage model where the output image quality of one stage is progressively improved in the next stage by using a triplet loss function.

Image Super-Resolution

Night Time Haze and Glow Removal using Deep Dilated Convolutional Network

no code implementations3 Feb 2019 Shiba Kuanar, K. R. Rao, Dwarikanath Mahapatra, Monalisa Bilas

The night haze removal is a severely ill-posed problem especially due to the presence of various visible light sources with varying colors and non-uniform illumination.

Single Image Haze Removal

Chest X-rays Classification: A Multi-Label and Fine-Grained Problem

no code implementations19 Jul 2018 Zongyuan Ge, Dwarikanath Mahapatra, Suman Sedai, Rahil Garnavi, Rajib Chakravorty

In this work we have proposed a novel error function, Multi-label Softmax Loss (MSML), to specifically address the properties of multiple labels and imbalanced data.

General Classification Image Classification

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

no code implementations14 Jun 2018 Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran, Mauricio Reyes

Training robust deep learning (DL) systems for medical image classification or segmentation is challenging due to limited images covering different disease types and severity.

Active Learning General Classification +1

GAN Based Medical Image Registration

no code implementations7 May 2018 Dwarikanath Mahapatra

Conventional approaches to image registration consist of time consuming iterative methods.

Image Registration Medical Image Registration

Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution

no code implementations13 Oct 2017 Dwarikanath Mahapatra, Behzad Bozorgtabar

We propose an image super resolution(ISR) method using generative adversarial networks (GANs) that takes a low resolution input fundus image and generates a high resolution super resolved (SR) image upto scaling factor of $16$.

Image Super-Resolution

Consensus Based Medical Image Segmentation Using Semi-Supervised Learning And Graph Cuts

no code implementations7 Dec 2016 Dwarikanath Mahapatra

A novel approach is proposed that obtains consensus segmentations from experts using graph cuts (GC) and semi supervised learning (SSL).

Medical Image Segmentation Semantic Segmentation

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