Title:
DIAGNOSIS SUPPORT DEVICE, DIAGNOSIS SUPPORT METHOD AND DIAGNOSIS SUPPORT PROGRAM
Document Type and Number:
WIPO Patent Application WO/2020/050272
Kind Code:
A1
Abstract:
This diagnosis support device (3), which supports a diagnosis of a vascular disease, includes: an image acquisition unit (341) which acquires an image including a cross section of a blood vessel; a line segment setting unit (342) which sets one or more line segments crossing the cross section; and a luminance distribution calculation unit (343) which calculates a luminance distribution on the line segment.
Inventors:
UEBA TETSUYA (JP)
MINAKUCHI KIYOMI (JP)
FUKUDA HITOSHI (JP)
MINAKUCHI KIYOMI (JP)
FUKUDA HITOSHI (JP)
Application Number:
PCT/JP2019/034623
Publication Date:
March 12, 2020
Filing Date:
September 03, 2019
Export Citation:
Assignee:
UNIV NAT CORP KOCHI UNIV (JP)
International Classes:
A61B5/055
Foreign References:
| JP2007275141A | 2007-10-25 | |||
| JP2010274059A | 2010-12-09 | |||
| JP2017074320A | 2017-04-20 | |||
| JP2013183875A | 2013-09-19 | |||
| US20190105008A1 | 2019-04-11 |
Other References:
WANG, DUO: "Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method", PROC. SPIE , MEDICAL IMAGING 2018, vol. 10574, 2 March 2018 (2018-03-02), pages 1057424 - 1-8, XP060103102
TAKEHARA, YASUO: "Magnetic Resonance Angiography of the Aorta", THE JOURNAL OF JAPANESE COLLEGE OF ANGIOLOGY , JAPANESE COLLEGE OF ANGIOLOGY, vol. 49, no. 6, 22 January 2010 (2010-01-22), pages 503 - 516, XP055689667
KAWAHARA, NOBUTAKA: "Medical Imaging Class for Clinical Residents, Cranial nerve area", IRYO KAGAKU SYA, 17 March 2008 (2008-03-17), pages 80 - 85
KATZ, WILLIAM T.: "AORTA DETECTION IN MAGNETIC RESONANCE IMAGE USING MULTIPLE ARTIFICIAL NEURAL NETWORKS", ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, vol. 12, no. 3, 1990, pages 1302 - 1303, XP055689664
KOVACS, TAMAS: "Automatic Segmentation of the Vessel Lumen from 3D CTA Images of Aortic Dissection", BILDVERARBEITUNG FUER DIE MEDIZIN, vol. 2006, 2006, pages 161 - 165, XP002479741, DOI: 10.1007/3-540-32137-3_33
MORARIU, COSMIN ADRIAN: "Sequential vs. Batch Machine-Learning with Evolutionary Hyperparameter Optimization for Segmenting Aortic Dissection Thrombus", 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, 2016, pages 1189 - 1194, XP033085749, DOI: 10.1109/ICPR.2016.7899798
LEE, NOAH: "True-false lumen segmentation of aortic dissection using multi-scale wavelet analysis and generative-discriminative model matching", PROC. SPIE, MEDICAL IMAGING 2008, vol. 6915, 17 March 2008 (2008-03-17), pages 69152V - 1-11, XP055689660
CHANG, CHIH-PING: "The role of False Lumen Size in Prediction of In-Hospital Complications After Acute Type B Aortic Dissection", JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, vol. 52, no. 14, 2008, pages 1170 - 1176, XP029650098, DOI: 10.1016/j.jacc.2008.06.034
LI, JIANNING: "Multi-Task Deep Convolutional Neural Network for the Segmentation of Type B Aortic Dissection", 26 June 2018 (2018-06-26), XP081039883, Retrieved from the Internet [retrieved on 20191118]
TAKEHARA, YASUO: "Magnetic Resonance Angiography of the Aorta", THE JOURNAL OF JAPANESE COLLEGE OF ANGIOLOGY , JAPANESE COLLEGE OF ANGIOLOGY, vol. 49, no. 6, 22 January 2010 (2010-01-22), pages 503 - 516, XP055689667
KAWAHARA, NOBUTAKA: "Medical Imaging Class for Clinical Residents, Cranial nerve area", IRYO KAGAKU SYA, 17 March 2008 (2008-03-17), pages 80 - 85
KATZ, WILLIAM T.: "AORTA DETECTION IN MAGNETIC RESONANCE IMAGE USING MULTIPLE ARTIFICIAL NEURAL NETWORKS", ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, vol. 12, no. 3, 1990, pages 1302 - 1303, XP055689664
KOVACS, TAMAS: "Automatic Segmentation of the Vessel Lumen from 3D CTA Images of Aortic Dissection", BILDVERARBEITUNG FUER DIE MEDIZIN, vol. 2006, 2006, pages 161 - 165, XP002479741, DOI: 10.1007/3-540-32137-3_33
MORARIU, COSMIN ADRIAN: "Sequential vs. Batch Machine-Learning with Evolutionary Hyperparameter Optimization for Segmenting Aortic Dissection Thrombus", 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, 2016, pages 1189 - 1194, XP033085749, DOI: 10.1109/ICPR.2016.7899798
LEE, NOAH: "True-false lumen segmentation of aortic dissection using multi-scale wavelet analysis and generative-discriminative model matching", PROC. SPIE, MEDICAL IMAGING 2008, vol. 6915, 17 March 2008 (2008-03-17), pages 69152V - 1-11, XP055689660
CHANG, CHIH-PING: "The role of False Lumen Size in Prediction of In-Hospital Complications After Acute Type B Aortic Dissection", JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, vol. 52, no. 14, 2008, pages 1170 - 1176, XP029650098, DOI: 10.1016/j.jacc.2008.06.034
LI, JIANNING: "Multi-Task Deep Convolutional Neural Network for the Segmentation of Type B Aortic Dissection", 26 June 2018 (2018-06-26), XP081039883, Retrieved from the Internet
Attorney, Agent or Firm:
SAEGUSA & PARTNERS (JP)
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