Presentation 2019-08-29
Severity Index Evaluation using Automatic Region of Interest Segmentation
Patinya Tantawiwat, Datchakorn Tancharoen, Toshihiko Yamasaki,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Psoriasis Area and Severity Index (PASI) is currently a standard approach to quantify severity of psoriasis. In this paper, we report an automatic region of interest (ROI) segmentation algorithm that can objectively measure the PASI score. The color space analysis is applied and K-mean clustering is used to separate the background from the skin region to segment the ROI from the normal skin. The experimental results using ten skin photo samples showed that the proposed method has low complexity and is practical to precisely detect the psoriasis area.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Medical imaging / Region of interest / Image segmentation / Psoriasis
Paper # MVE2019-5
Date of Issue 2019-08-22 (MVE)

Conference Information
Committee MVE
Conference Date 2019/8/29(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Kenji Mase(Nagoya Univ.)
Vice Chair Masayuki Ihara(NTT)
Secretary Masayuki Ihara(Nagoya Univ.)
Assistant Satoshi Nishiguchi(Oosaka Inst. of Tech.) / Masanori Yokoyama(NTT) / Shogo Fukushima(Univ. of ToKyo)

Paper Information
Registration To Technical Committee on Media Experience and Virtual Environment
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Severity Index Evaluation using Automatic Region of Interest Segmentation
Sub Title (in English)
Keyword(1) Medical imaging
Keyword(2) Region of interest
Keyword(3) Image segmentation
Keyword(4) Psoriasis
1st Author's Name Patinya Tantawiwat
1st Author's Affiliation Panyapiwat Institute of Management(PIM)
2nd Author's Name Datchakorn Tancharoen
2nd Author's Affiliation Panyapiwat Institute of Management(PIM)
3rd Author's Name Toshihiko Yamasaki
3rd Author's Affiliation The University of Tokyo(UTokyo)
Date 2019-08-29
Paper # MVE2019-5
Volume (vol) vol.119
Number (no) MVE-190
Page pp.pp.13-16(MVE),
#Pages 4
Date of Issue 2019-08-22 (MVE)