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Automated segmentat...
Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis
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- Moshavegh, Ramin (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Ehteshami Bejnordi, B. (author)
- Uppsala universitet,Bildanalys och människa-datorinteraktion
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- Mehnert, Andrew, 1967 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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Sujathan, K. (author)
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- Malm, Patrik (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Uppsala University
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- Bengtsson, Ewert (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion
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(creator_code:org_t)
- ISBN 9781424441198
- 2012
- 2012
- English.
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In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 5372-5375
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Abstract
Subject headings
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- This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Keyword
- Microscope images
- Pap smear
- Manual segmentation
- Automated algorithms
- Sensitivity and specificity
- Change analysis
- Watershed segmentation
- Dice coefficient
- Automated segmentation
- Gray scale
- Cervical cancers
- Automated screening
- Cell nucleus
- Segmentation algorithms
- Epithelial cells
- Brightfield
- Datoriserad bildanalys
Publication and Content Type
- kon (subject category)
- ref (subject category)
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