Sökning: onr:"swepub:oai:DiVA.org:uu-469951" > Automated detection...
Fältnamn | Indikatorer | Metadata |
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000 | 04263naa a2200493 4500 | |
001 | oai:DiVA.org:uu-469951 | |
003 | SwePub | |
008 | 220316s2022 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4699512 URI |
024 | 7 | a https://doi.org/10.1002/path.59812 DOI |
040 | a (SwePub)uu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a art2 swepub-publicationtype |
100 | 1 | a Bekkhus, Toveu Uppsala universitet,Vaskulärbiologi4 aut0 (Swepub:uu)tovbe228 |
245 | 1 0 | a Automated detection of vascular remodeling in human tumor draining lymph nodes by the deep learning tool HEV-finder |
264 | c 2022-07-12 | |
264 | 1 | b John Wiley & Sons,c 2022 |
338 | a electronic2 rdacarrier | |
520 | a Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. | |
650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Cancer och onkologi0 (SwePub)302032 hsv//swe |
650 | 7 | a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cancer and Oncology0 (SwePub)302032 hsv//eng |
653 | a HEV-finder | |
653 | a artificial intelligence (AI) | |
653 | a breast cancer | |
653 | a deep learning | |
653 | a high endothelial venules (HEVs) | |
653 | a tumor-draining lymph nodes (TDLNs) | |
653 | a vascular remodeling | |
700 | 1 | a Avenel, Christopheu Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion4 aut0 (Swepub:uu)chrav452 |
700 | 1 | a Hanna, Sabellau Uppsala universitet,Vaskulärbiologi4 aut |
700 | 1 | a Franzén Boger, Mathiasu Uppsala universitet,Institutionen för immunologi, genetik och patologi4 aut |
700 | 1 | a Klemm, Anna Hu Uppsala universitet,Avdelningen för visuell information och interaktion,Science for Life Laboratory, SciLifeLab4 aut0 (Swepub:uu)annkl878 |
700 | 1 | a Vasiliu-Bacovia, Danielu Uppsala universitet,Institutionen för immunologi, genetik och patologi4 aut0 (Swepub:uu)danva511 |
700 | 1 | a Wärnberg, Fredriku Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden4 aut0 (Swepub:uu)fredwarn |
700 | 1 | a Wählby, Carolina,c professor,d 1974-u Uppsala universitet,Bildanalys och människa-datorinteraktion,Science for Life Laboratory, SciLifeLab,Avdelningen för visuell information och interaktion4 aut0 (Swepub:uu)cli05194 |
700 | 1 | a Ulvmar, Maria H.u Uppsala universitet,Vaskulärbiologi4 aut0 (Swepub:uu)marul414 |
710 | 2 | a Uppsala universitetb Vaskulärbiologi4 org |
773 | 0 | t Journal of Pathologyd : John Wiley & Sonsg 258:1, s. 4-11q 258:1<4-11x 0022-3417x 1096-9896 |
856 | 4 | u https://doi.org/10.1002/path.5981y Fulltext |
856 | 4 | u https://uu.diva-portal.org/smash/get/diva2:1645277/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-469951 |
856 | 4 8 | u https://doi.org/10.1002/path.5981 |
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