Shifting representations: Adventures in cross-modality domain adaptation for medical image analysis

Gijs van Tulder

Shifting representations: Adventures in cross-modality domain adaptation for medical image analysis

Gijs van Tulder

Radiology & Nuclear Medicine

Research output: Types of Thesis › Doctoral Thesis › Internal

337 Downloads (Pure)

Abstract

Dit proefschrift onderzoekt methodes voor domeinadaptatie voor medische beeldanalyse tussen verschillende beeldmodaliteiten, op basis van deep learning en representation learning. De methodes worden geëvalueerd op verschillende taken, zoals longweefselclassificatie en tumorsegmentatie.

Original language	English
Awarding Institution	Erasmus University Rotterdam
Supervisors/Advisors	de Bruijne, Marleen, Supervisor Niessen, Wiro, Supervisor
Award date	14 Jun 2022
Place of Publication	Rotterdam
Print ISBNs	978-94-6423-793-1
Publication status	Published - 14 Jun 2022

Bibliographical note

Most of the research in this thesis was funded by the Netherlands Organization for Scientific Research (NWO), as part of the VIDI project “Transfer learning in biomedical image analysis” (number 639.022.010)

Access to Document

final dissertation Van TulderFinal published version, 5.31 MB

Cite this

@phdthesis{cecfcba0453c40b4bba58f815b288601,

title = "Shifting representations: Adventures in cross-modality domain adaptation for medical image analysis",

abstract = "Dit proefschrift onderzoekt methodes voor domeinadaptatie voor medische beeldanalyse tussen verschillende beeldmodaliteiten, op basis van deep learning en representation learning. De methodes worden ge{\"e}valueerd op verschillende taken, zoals longweefselclassificatie en tumorsegmentatie.",

author = "\{van Tulder\}, Gijs",

note = "Most of the research in this thesis was funded by the Netherlands Organization for Scientific Research (NWO), as part of the VIDI project “Transfer learning in biomedical image analysis” (number 639.022.010)",

year = "2022",

month = jun,

day = "14",

language = "English",

isbn = "978-94-6423-793-1",

series = "ASCI Dissertation Series",

number = "435",

school = "Erasmus University Rotterdam",

}

TY - BOOK

T1 - Shifting representations

T2 - Adventures in cross-modality domain adaptation for medical image analysis

AU - van Tulder, Gijs

N1 - Most of the research in this thesis was funded by the Netherlands Organization for Scientific Research (NWO), as part of the VIDI project “Transfer learning in biomedical image analysis” (number 639.022.010)

PY - 2022/6/14

Y1 - 2022/6/14

N2 - Dit proefschrift onderzoekt methodes voor domeinadaptatie voor medische beeldanalyse tussen verschillende beeldmodaliteiten, op basis van deep learning en representation learning. De methodes worden geëvalueerd op verschillende taken, zoals longweefselclassificatie en tumorsegmentatie.

AB - Dit proefschrift onderzoekt methodes voor domeinadaptatie voor medische beeldanalyse tussen verschillende beeldmodaliteiten, op basis van deep learning en representation learning. De methodes worden geëvalueerd op verschillende taken, zoals longweefselclassificatie en tumorsegmentatie.

UR - https://www.vantulder.net/

M3 - Doctoral Thesis

SN - 978-94-6423-793-1

T3 - ASCI Dissertation Series

CY - Rotterdam

ER -

Shifting representations: Adventures in cross-modality domain adaptation for medical image analysis

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this