A Deep Learning Based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images

Lu, JiahaoUppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion (author)

Oral cancer incidence is rapidly increasing worldwide. The most important determinant factor in cancer survival is early diagnosis. To facilitate large scale screening, we propose a fully automated pipeline for oral cancer detection on whole slide cytology images. The pipeline consists of fully convolutional regression-based nucleus detection, followed by per-cell focus selection, and CNN based classification. Our novel focus selection step provides fast per-cell focus decisions at human-level accuracy. We demonstrate that the pipeline provides efficient cancer classification of whole slide cytology images, improving over previous results both in terms of accuracy and feasibility. The complete source code is made available as open source (https://github.com/MIDA-group/OralScreen).

TEKNIK OCH TEKNOLOGIER Medicinteknik Medicinsk bildbehandling hsv//swe
ENGINEERING AND TECHNOLOGY Medical Engineering Medical Image Processing hsv//eng
CNN
Whole slide imaging
Big data
Cytology
Detection
Focus selection
Classification
Datoriserad bildbehandling
Computerized Image Processing

Sladoje, NatasaUppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion(Swepub:uu)namat934 (author)
Runow Stark, Christina (author)
Darai Ramqvist, Eva (author)
Hirsch, Jan-Michaél (author)
Lindblad, JoakimUppsala universitet,Bildanalys och människa-datorinteraktion,Avdelningen för visuell information och interaktion(Swepub:uu)joali534 (author)
Uppsala universitetAvdelningen för visuell information och interaktion (creator_code:org_t)

In:Image Analysis and RecognitionCham : Springer International Publishing, s. 249-26197830305051589783030505165

By the author/editor: Lu, Jiahao; Sladoje, Natasa; Runow Stark, Chr ...; Darai Ramqvist, ...; Hirsch, Jan-Mich ...; Lindblad, Joakim

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Medical Engineer ...; and Medical Image Pr ...

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