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Whole Slide Image R...
Whole Slide Image Registration for the Study of Tumor Heterogeneity
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- Solorzano, Leslie, 1989- (författare)
- Uppsala universitet,Avdelningen för visuell information och interaktion
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- Almeida, Gabriela (författare)
- Ipatimup, Institute of Molecular Pathology and ImmunologyUniversity of Porto,i3S Instituto de Investigação e Inovação em Saúde Universidade do Porto Portugal
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- Mesquita, Bárbara (författare)
- i3S Instituto de Investigação e Inovação em Saúde Universidade do Porto Portugal
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- Martins, Diana (författare)
- i3S Instituto de Investigação e Inovação em Saúde Universidade do Porto Portugal
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- Oliveira, Carla (författare)
- i3S Instituto de Investigação e Inovação em Saúde Universidade do Porto Portugal
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- Wählby, Carolina, 1974- (författare)
- Uppsala universitet,Bildanalys och människa-datorinteraktion
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(creator_code:org_t)
- 2018-09-14
- 2018
- Engelska.
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Ingår i: MICCAI 2018 - International Workshop on Ophthalmic Medical Image Analysis. - Cham : Springer. - 9783030009496 - 9783030009489 ; , s. 95-102
- Relaterad länk:
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https://www.miccai20...
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http://arxiv.org/pdf...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Consecutive thin sections of tissue samples make it possible to study local variation in e.g. protein expression and tumor heterogeneity by staining for a new protein in each section. In order to compare and correlate patterns of different proteins, the images have to be registered with high accuracy. The problem we want to solve is registration of gigapixel whole slide images (WSI). This presents 3 challenges: (i) Images are very large; (ii) Thin sections result in artifacts that make global affine registration prone to very large local errors; (iii) Local affine registration is required to preserve correct tissue morphology (local size, shape and texture). In our approach we compare WSI registration based on automatic and manual feature selection on either the full image or natural sub-regions (as opposed to square tiles). Working with natural sub-regions, in an interactive tool makes it possible to exclude regions containing scientifically irrelevant information. We also present a new way to visualize local registration quality by a Registration Confidence Map (RCM). With this method, intra-tumor heterogeneity and characteristics of the tumor microenvironment can be observed and quantified.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Nyckelord
- WSI
- digital pathology
- registration
- whole slide image
- Computerized Image Processing
- Datoriserad bildbehandling
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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