| Project/Area Number |
08680408
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | SAPPORO MEDICAL UNIVERSITY |
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Principal Investigator |
NATORI Hiroshi Sapporo Medical University School of Medicine, Department of Diagnostic Ultrasound and ME,Professor, 医学部, 教授 (00102260)
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| Co-Investigator(Kenkyū-buntansha) |
MITANI Masanobu Sapporo Medical University School of Medicine, Department of Diagnostic Ultrasou, 医学部, 助手 (70200061)
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| Project Period (FY) |
1996 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,600,000)
Fiscal Year 1997: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 1996: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | lung cancer / chest radiogram / computed tomography / computerized diagnosis / image recognition / pulmonary nodule / radiologic anatomy / 解剖学的知識ベース / 肺血管構造 / ヘリカルCT像 / 自動診断 / 質的診断 / 肺腫瘤影 / 肺癌 |
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| Research Abstract |
Discrimination of false positive shadow is important in an automatic diagnosis system for nodular shadow of the peripheral lung on chest radiogram or on chest CT.In an image recognition study by computed analysis system, nodular shadow of the cancer revealed an output value that looks like those of the shadows of the blood vessels on the chest radiogram. It is difficult to identify those images by analytical technique using specially designed extraction filter and elimination at an appropriate threshold level. Construction of the knowledge database of medical images based on the 3-dimensional anatomy is an aim of this study to establish a detection method for pulmonary nodules and an elimination method for false positive shadows. [Methods and Results]
1)Kowledge database of images based on the 3-dimensional anatomy
An anatomical knowledge base which has length and information of direction of blood vessels was originally created. It includes information from the hilum to the periphery ref
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lecting original branching pattern of the blood vessels. As a model of knowledge base, a combination of prevalence patterns that created by Yamashita was used in this study. Length of the vessels were decided as the length of the right main bronchus was set to three units. Directions was 3-dimensionally demonstrated as one of 26 directions. Continuity of the vessels was shown as parent-children-grandchildren relationships.
2)Decision of blood vessels on the basis of anatomical knowledge base
Decision algorithm of the blood vessels on the basis of anatomical knowledge base which has information of length, direction, and continuity was created. However, it was impossible to name vessels on only this anatomical knowledge database.
3)Automated detection system for pulmonary nodules
Using chest helical CT image, an automated detection system for pulmonary nodules has been developed. To detect nodules on CT images, we use the directional contrast filter for nodule (DCF-N) which was developed for chest radiograms and its parameters were modified for CT images. Nodules of 87.5% was successfully detected by this system, however, many falsepositive foci was detected by this system. Including information of vascular anatomy, it will be possible to reduce false-positives and improve the differential diagnostic value of this system. [Conclusions]
The ability of this system to recognition blood vessels may not be sufficient for future use. One of the reason of this situation might be due to insufficient information that correspond to multiple branching pattern models of the arterial tree. There was a difficulty to differentiate pulmonary arteries from veins by the information of length, direction, and continuity. Information of lobar position of the vessels must be defined in the system. As for nodule detection, the system fairly detected nodular opacities which have three-concentric circular structures. Less
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