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- Blondel, A., et al.
(författare)
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The SuperFGD Prototype charged particle beam tests
- 2020
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Ingår i: Journal of Instrumentation. - : IOP PUBLISHING LTD. - 1748-0221 .- 1748-0221. ; 15:12
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Tidskriftsartikel (refereegranskat)abstract
- A novel scintillator detector, the SuperFGD, has been selected as the main neutrino target for an upgrade of the T2K experiment ND280 near detector. The detector design will allow nearly 47r coverage for neutrino interactions at the near detector and will provide lower energy thresholds, significantly reducing systematic errors for the experiment. The SuperFGD is made of optically-isolated scintillator cubes of size 10 x 10 x 10 mm(3), providing the required spatial and energy resolution to reduce systematic uncertainties for future T2K runs. The SuperFGD for T2K will have close to two million cubes in a 1920 x 560 x 1840 mm(3) volume. A prototype made of 24 x 8 x 48 cubes was tested at a charged particle beamline at the CERN PS facility. The SuperFGD Prototype was instrumented with readout electronics similar to the future implementation for T2K. Results on electronics and detector response are reported in this paper, along with a discussion of the 3D reconstruction capabilities of this type of detector. Several physics analyses with the prototype data are also discussed, including a study of stopping protons.
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| 2. |
- Smedsrud, P. H., et al.
(författare)
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Kvasir-Capsule, a video capsule endoscopy dataset
- 2021
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates the promising benefits of AI-based computer-assisted diagnosis systems for VCE. They also show great potential for improvements to achieve even better results. Also, medical data is often sparse and unavailable to the research community, and qualified medical personnel rarely have time for the tedious labelling work. We present Kvasir-Capsule, a large VCE dataset collected from examinations at a Norwegian Hospital. Kvasir-Capsule consists of 117 videos which can be used to extract a total of 4,741,504 image frames. We have labelled and medically verified 47,238 frames with a bounding box around findings from 14 different classes. In addition to these labelled images, there are 4,694,266 unlabelled frames included in the dataset. The Kvasir-Capsule dataset can play a valuable role in developing better algorithms in order to reach true potential of VCE technology.
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| 4. |
- Borgli, H, et al.
(författare)
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HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy
- 2020
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Ingår i: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7:1, s. 283-
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually label training data. These constraints make it difficult to develop systems for automatic analysis, like detecting disease or other lesions. In this respect, this article presents HyperKvasir, the largest image and video dataset of the gastrointestinal tract available today. The data is collected during real gastro- and colonoscopy examinations at Bærum Hospital in Norway and partly labeled by experienced gastrointestinal endoscopists. The dataset contains 110,079 images and 374 videos, and represents anatomical landmarks as well as pathological and normal findings. The total number of images and video frames together is around 1 million. Initial experiments demonstrate the potential benefits of artificial intelligence-based computer-assisted diagnosis systems. The HyperKvasir dataset can play a valuable role in developing better algorithms and computer-assisted examination systems not only for gastro- and colonoscopy, but also for other fields in medicine.
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