Search Results for author: Jens Rittscher

Found 19 papers, 6 papers with code

EndoUDA: A modality independent segmentation approach for endoscopy imaging

no code implementations12 Jul 2021 Numan Celik, Sharib Ali, Soumya Gupta, Barbara Braden, Jens Rittscher

While, today most segmentation approaches are supervised and only concentrated on a single modality dataset, this work exploits to use a target-independent unsupervised domain adaptation (UDA) technique that is capable to generalize to an unseen target modality.

Unsupervised Domain Adaptation

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation

1 code implementation31 Mar 2021 Nikhil Kumar Tomar, Debesh Jha, Michael A. Riegler, Håvard D. Johansen, Dag Johansen, Jens Rittscher, Pål Halvorsen, Sharib Ali

We propose a novel architecture called feedback attention network (FANet) that unifies the previous epoch mask with the feature map of the current training epoch.

Hard Attention Medical Image Segmentation +1

Microscopic fine-grained instance classification through deep attention

no code implementations6 Oct 2020 Mengran Fan, Tapabrata Chakrabort, Eric I-Chao Chang, Yan Xu, Jens Rittscher

Fine-grained classification of microscopic image data with limited samples is an open problem in computer vision and biomedical imaging.

Deep Attention General Classification +1

Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images

no code implementations23 Mar 2020 Sharib Ali, Binod Bhattarai, Tae-Kyun Kim, Jens Rittscher

In this work, we propose to use a few-shot learning approach that requires less training data and can be used to predict label classes of test samples from an unseen dataset.

Few-Shot Learning

Semantic filtering through deep source separation on microscopy images

1 code implementation2 Sep 2019 Avelino Javer, Jens Rittscher

By their very nature microscopy images of cells and tissues consist of a limited number of object types or components.

Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping

no code implementations16 Aug 2019 Sharib Ali, Jens Rittscher

To address this problem, we propose a novel approach of learning a continuous warp of the source image.

Image Registration

Ink removal from histopathology whole slide images by combining classification, detection and image generation models

1 code implementation10 May 2019 Sharib Ali, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher

Removal of marker ink from these high-resolution whole slide images is non-trivial and complex problem as they contaminate different regions and in an inconsistent manner.

General Classification Image Generation +1

A deep learning framework for quality assessment and restoration in video endoscopy

no code implementations15 Apr 2019 Sharib Ali, Felix Zhou, Adam Bailey, Barbara Braden, James East, Xin Lu, Jens Rittscher

Given the widespread use of endoscopy in different clinical applications, we contend that the robust and reliable identification of such artifacts and the automated restoration of corrupted video frames is a fundamental medical imaging problem.

Deblurring Frame +1

Improving Whole Slide Segmentation Through Visual Context - A Systematic Study

1 code implementation11 Jun 2018 Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher

While challenging, the dense segmentation of histology images is a necessary first step to assess changes in tissue architecture and cellular morphology.

General Classification Image Classification

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