Sökning: WFRF:(Strand Robin 1978 ) > (2020-2024) > Segmentation of Maj...
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000 | 03381naa a2200361 4500 | |
001 | oai:DiVA.org:uu-490226 | |
003 | SwePub | |
008 | 221208s2022 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4902262 URI |
024 | 7 | a https://doi.org/10.1109/CATCON56237.2022.100777112 DOI |
040 | a (SwePub)uu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a kon2 swepub-publicationtype |
100 | 1 | a Pal, Subhashu National Institute of Technology, Durgapur, India4 aut |
245 | 1 0 | a Segmentation of Major Cerebral Vessel from MRA images and Evaluation using U-Net Family |
264 | 1 | b Institute of Electrical and Electronics Engineers (IEEE),c 2022 |
338 | a print2 rdacarrier | |
520 | a Arterial cerebral vessel assessment is critical for thediagnosis of patients with cerebrovascular disease e.g., hypertension, Intracranial aneurysms, and dementia. Magnetic resonance angiography is a primary imaging technique for diagnosing cerebrovascular diseases. There are many Convolutional neuralnetworks (CNN) based methods for cerebral vessel segmentation but lack to identify the target vessels and understand the arterial tree structure for diagnosis and endovascular surgical planning.In the present study, we generated annotations for major vesselsegmentation and analyzed fully automatic segmentation of major vessels using state-of-the-art U-Net based deep learning models. Computer-aided major cerebral vessel segmentation incorporatedinto clinical practice may help speed up the diagnosis of time-critical vessel anomalies and help find important bio-markers for neurological dysfunction. We validated and compared U-Net based models for volumetric segmentation and predictionof cerebral arteries and it could be done in real-time withoutany image pre-processing. | |
650 | 7 | a TEKNIK OCH TEKNOLOGIERx Medicinteknikx Medicinsk bildbehandling0 (SwePub)206032 hsv//swe |
650 | 7 | a ENGINEERING AND TECHNOLOGYx Medical Engineeringx Medical Image Processing0 (SwePub)206032 hsv//eng |
650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Radiologi och bildbehandling0 (SwePub)302082 hsv//swe |
650 | 7 | a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Radiology, Nuclear Medicine and Medical Imaging0 (SwePub)302082 hsv//eng |
700 | 1 | a Banerjee, Subhashisu Uppsala universitet,Bildanalys och människa-datorinteraktion4 aut0 (Swepub:uu)subba385 |
700 | 1 | a Toumpanakis, Dimitriosu Uppsala universitet,Radiologi4 aut0 (Swepub:uu)dimto708 |
700 | 1 | a Wikström, Johan,c Professor,d 1964-u Uppsala universitet,Radiologi4 aut0 (Swepub:uu)jwi06759 |
700 | 1 | a Strand, Robin,d 1978-u Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion4 aut0 (Swepub:uu)rostr275 |
700 | 1 | a Dhara, Ashisu National Institute of Technology, Durgapur, India4 aut |
710 | 2 | a National Institute of Technology, Durgapur, Indiab Bildanalys och människa-datorinteraktion4 org |
773 | 0 | t 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON)d : Institute of Electrical and Electronics Engineers (IEEE)g , s. 235-238q <235-238z 9781665473804 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-490226 |
856 | 4 8 | u https://doi.org/10.1109/CATCON56237.2022.10077711 |
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