366 citations
- University of OsloNO44 papers
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- OsloMet – Oslo Metropolitan UniversityNO3 papers
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5 papers · 1 filter
Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?
Hemin Ali Qadir, Younghak Shin, Johannes Solhusvik +3
Automatic polyp detection and segmentation are highly desirable for colon screening due to polyp miss rate by physicians during colonoscopy, which is about 25%. However, this compu…
Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
Younghak Shin, Hemin Ali Qadir, Ilangko Balasingham
One of the major obstacles in automatic polyp detection during colonoscopy is the lack of labeled polyp training images. In this paper, we propose a framework of conditional advers…
Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches
Younghak Shin, Hemin Ali Qadir, Lars Aabakken +2
Automatic detection of colonic polyps is still an unsolved problem due to the large variation of polyps in terms of shape, texture, size, and color, and the existence of various po…
Diverse personalized recommendations with uncertainty from implicit preference data with the Bayesian Mallows Model
Qinghua Liu, Andrew Henry Reiner, Arnoldo Frigessi +1
Clicking data, which exists in abundance and contains objective user preference information, is widely used to produce personalized recommendations in web-based applications. Curre…
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI
Endre Grøvik, Darvin Yi, Michael Iv +3
Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-sequence 3D imaging. This study dem…