CONTROL METHOD, INFORMATION TERMINAL AND PROGRAM

Japanese Patent JP2018102916

A

PROBLEM TO BE SOLVED: To efficiently determine a lesion area.SOLUTION: A probability image calculation part 102 calculates a probability value that a pixel of each of specified object images is included in a lesion area when a lesion included in the specified object image is a texture type lesion. An output part 103 calculates an area consisting of pixels having a probability value of a first threshold or higher as a candidate area in a probability image acquired from the probability image calculation part 102, and calculates an area consisting of pixels having a probability value in a specific probability range including the first threshold. An input part 104 detects a user's input to pixels of a corrected area which the output part 103 displays in a display by operation of an operation device. A lesion area specification part 105 specifies the lesion area on the basis of the probability image acquired from the probability image calculation part 102, the candidate area and the corrected area acquired from the output part 103 and user operation information acquired from the input part 104.SELECTED DRAWING: Figure 1

WAKASUGI KENSUKE
KONDO KENJI
TAKADA KAZUTOYO
KIMURA HIROHIKO
SAKAI TOYOHIKO

JP2017236876A

July 05, 2018

December 11, 2017

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PANASONIC IP MAN CORP

A61B6/03; G06T1/00; G06T7/00; G06V10/25; G06V10/50; G06V10/764

JP2012090669A	2012-05-17
JP2005028051A	2005-02-03
JP2006334404A	2006-12-14
JP2016193295A	2016-11-17

鈴木　聡志　他２名: "”びまん性肺疾患識別におけるＤｅｅｐ　Ｃｏｎｖｏｌｕｔｉｏｎａｌ　Ｎｅｕｒａｌ　Ｎｅｔｗｏｒｋ特徴の", 情報処理学会研究報告（ＩＰＳＪ　ＳＩＧ　ＴＥＣＨＮＩＣＡＬ　ＲＥＰＯＲＴ）, vol. Vol.2015-MPS-103, No.29, JPN6021030593, 24 June 2015 (2015-06-24), pages 1 - 6, ISSN: 0004566493

Etsushi Kotani
Masataka Otani
Koji Nishitani

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