Development of CAD scheme for automated detection of intracranial aneurysms in magnetic resonance angiography

Hidetaka Arimura; Qiang Li; Yukunori Korogi; Toshinori Hirai; Hiroyuki Abe; Yasuyuki Yamashita; Shigehiko Katsuragawa; Ryuji Ikeda; Kunio Doi

doi:10.1016/j.ics.2004.03.102

Development of CAD scheme for automated detection of intracranial aneurysms in magnetic resonance angiography

Hidetaka Arimura, Qiang Li, Yukunori Korogi, Toshinori Hirai, Hiroyuki Abe, Yasuyuki Yamashita, Shigehiko Katsuragawa, Ryuji Ikeda, Kunio Doi

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

We have developed a computer-aided diagnostic (CAD) scheme for automated detection of intracranial aneurysms in magnetic resonance angiography (MRA). A total of 29 cases with 36 aneurysms and 31 non-aneurysm cases were processed by use of the selective enhancement filter for dots (aneurysms). All candidates were classified into four types according to the size and local structures based on the effective diameter and the skeleton image of each candidate. A number of false positives were removed in each group by use of rule-based schemes and linear discriminant analysis. All of 36 aneurysms were correctly detected with 0.55 false positives per patient. The CAD scheme would be useful in assisting radiologists for detection of intracranial aneurysms in MRA.

Original language	English
Pages (from-to)	1015-1020
Number of pages	6
Journal	International Congress Series
Volume	1268
Issue number	C
DOIs	https://doi.org/10.1016/j.ics.2004.03.102
Publication status	Published - Jun 1 2004
Externally published	Yes

All Science Journal Classification (ASJC) codes

Medicine(all)

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10.1016/j.ics.2004.03.102

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title = "Development of CAD scheme for automated detection of intracranial aneurysms in magnetic resonance angiography",

abstract = "We have developed a computer-aided diagnostic (CAD) scheme for automated detection of intracranial aneurysms in magnetic resonance angiography (MRA). A total of 29 cases with 36 aneurysms and 31 non-aneurysm cases were processed by use of the selective enhancement filter for dots (aneurysms). All candidates were classified into four types according to the size and local structures based on the effective diameter and the skeleton image of each candidate. A number of false positives were removed in each group by use of rule-based schemes and linear discriminant analysis. All of 36 aneurysms were correctly detected with 0.55 false positives per patient. The CAD scheme would be useful in assisting radiologists for detection of intracranial aneurysms in MRA.",

author = "Hidetaka Arimura and Qiang Li and Yukunori Korogi and Toshinori Hirai and Hiroyuki Abe and Yasuyuki Yamashita and Shigehiko Katsuragawa and Ryuji Ikeda and Kunio Doi",

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AU - Arimura, Hidetaka

AU - Li, Qiang

AU - Korogi, Yukunori

AU - Hirai, Toshinori

AU - Abe, Hiroyuki

AU - Yamashita, Yasuyuki

AU - Katsuragawa, Shigehiko

AU - Ikeda, Ryuji

AU - Doi, Kunio

PY - 2004/6/1

Y1 - 2004/6/1

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AB - We have developed a computer-aided diagnostic (CAD) scheme for automated detection of intracranial aneurysms in magnetic resonance angiography (MRA). A total of 29 cases with 36 aneurysms and 31 non-aneurysm cases were processed by use of the selective enhancement filter for dots (aneurysms). All candidates were classified into four types according to the size and local structures based on the effective diameter and the skeleton image of each candidate. A number of false positives were removed in each group by use of rule-based schemes and linear discriminant analysis. All of 36 aneurysms were correctly detected with 0.55 false positives per patient. The CAD scheme would be useful in assisting radiologists for detection of intracranial aneurysms in MRA.

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Development of CAD scheme for automated detection of intracranial aneurysms in magnetic resonance angiography

Abstract

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