Search Results for author: Mattias Heinrich

Found 6 papers, 2 papers with code

Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization

no code implementations20 May 2022 Abhishek Dinkar Jagtap, Mattias Heinrich, Marian Himstedt

An increasing number of colonoscopic guidance and assistance systems rely on machine learning algorithms which require a large amount of high-quality training data.

Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking

no code implementations5 Dec 2018 Alessa Hering, Sven Kuckertz, Stefan Heldmann, Mattias Heinrich

While deep learning has achieved significant advances in accuracy for medical image segmentation, its benefits for deformable image registration have so far remained limited to reduced computation times.

Image Registration Medical Image Segmentation +1

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

2 code implementations22 Aug 2018 Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert

AGs can be easily integrated into standard CNN models such as VGG or U-Net architectures with minimal computational overhead while increasing the model sensitivity and prediction accuracy.

General Classification Image Classification

Attention U-Net: Learning Where to Look for the Pancreas

27 code implementations11 Apr 2018 Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert

We propose a novel attention gate (AG) model for medical imaging that automatically learns to focus on target structures of varying shapes and sizes.

Brain Tumor Segmentation Pancreas Segmentation +1

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