Search Results for author: Thomas de Lange

Found 8 papers, 6 papers with code

A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation

1 code implementation26 Jul 2021 Debesh Jha, Pia H. Smedsrud, Dag Johansen, Thomas de Lange, Håvard D. Johansen, Pål Halvorsen, Michael A. Riegler

To explore the generalization capability of ResUNet++ on different publicly available polyp datasets, so that it could be used in a real-world setting, we performed an extensive cross-dataset evaluation.

Medical Image Segmentation

SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation

1 code implementation29 Jun 2021 Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A. Hicks, Hugo L. Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, Michael A. Riegler

We show that these synthetic data generation pipelines can be used as an alternative to bypass privacy concerns and as an alternative way to produce artificial segmentation datasets with corresponding ground truth masks to avoid the tedious medical data annotation process.

Medical Image Segmentation Synthetic Data Generation

NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy

1 code implementation22 Apr 2021 Debesh Jha, Nikhil Kumar Tomar, Sharib Ali, Michael A. Riegler, Håvard D. Johansen, Dag Johansen, Thomas de Lange, Pål Halvorsen

To utilize automated methods in clinical settings, it is crucial to design lightweight models with low latency such that they can be integrated with low-end endoscope hardware devices.

Colorectal Polyps Characterization Instrument Recognition +3

ResUNet++: An Advanced Architecture for Medical Image Segmentation

6 code implementations16 Nov 2019 Debesh Jha, Pia H. Smedsrud, Michael A. Riegler, Dag Johansen, Thomas de Lange, Pal Halvorsen, Havard D. Johansen

Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing into cancer.

Colorectal Polyps Characterization Medical Image Segmentation +1

Kvasir-SEG: A Segmented Polyp Dataset

no code implementations16 Nov 2019 Debesh Jha, Pia H. Smedsrud, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Dag Johansen, Håvard D. Johansen

In this paper, we present Kvasir-SEG: an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an experienced gastroenterologist.

 Ranked #1 on Polyp Segmentation on Kvasir-SEG (DSC metric)

Medical Image Segmentation Polyp Segmentation

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