2006
DOI: 10.1093/ietisy/e89-d.1.340
|View full text |Cite
|
Sign up to set email alerts
|

Computer-Aided Diagnosis of Intracranial Aneurysms in MRA Images with Case-Based Reasoning

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
26
0

Year Published

2009
2009
2022
2022

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 32 publications
(26 citation statements)
references
References 15 publications
0
26
0
Order By: Relevance
“…4 Only few methods have been proposed to detect cerebral aneurysms in medical images. [5][6][7][8] All algorithms rely on a two-step strategy that first detects potential regions based on a segmented vasculature and then use a classifier to reduce false positives (FP). Three different strategies are employed for initial findings: shape-based, skeleton-based and difference image based approaches.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…4 Only few methods have been proposed to detect cerebral aneurysms in medical images. [5][6][7][8] All algorithms rely on a two-step strategy that first detects potential regions based on a segmented vasculature and then use a classifier to reduce false positives (FP). Three different strategies are employed for initial findings: shape-based, skeleton-based and difference image based approaches.…”
Section: Introductionmentioning
confidence: 99%
“…5,7 Difference image based approaches use a subtraction of a normal vessel model from the original data set to find suspicious regions. 8 The challenge is to find abnormalities in the angiographic data sets as the intra-patient vessel variability is high. Hybrid approaches that use a combination In the CTA example, a clipping plane has been chosen to visualize blood vessels inside the skull.…”
Section: Introductionmentioning
confidence: 99%
“…Stand-alone performance figures of various CAD algorithms for cerebral aneurysms have been studied mainly by using datasets of known aneurysms, and high sensitivities have been reported. [10][11][12][13] Previous observer performance studies showed that CAD for cerebral aneurysms raises the sensitivity of radiologists 14,15 or reduces reading time while maintaining the sensitivity. 16 However, those studies were performed under experimental conditions with a relatively small number of aneurysms.…”
mentioning
confidence: 99%
“…However, it is difficult and time consuming for radiologists to detect small aneurysms, because of their overlap with adjacent vessels or unusual locations in maximum intensity projection (MIP) images of MRA. Therefore, a number of CAD systems have been developed for assisting radiologists in detection of intracranial aneurysms [25,26,41,65,66]. Table 1 shows a comparison of methods and results of CAD systems for detection of intracranial aneurysms using MRA.…”
Section: Intracranial Aneurysmmentioning
confidence: 99%
“…Table 1 shows a comparison of methods and results of CAD systems for detection of intracranial aneurysms using MRA. Kobashi et al [66] proposed a CAD system for detecting intracranial aneurysms in MRA images based on estimation of the fuzzy degrees for each aneurysm candidate, which denoted whether a candidate is an aneurysm. Hayashi et al [41] developed a curvature-based display system that shows volume-rendered images with overlaid curvature indices determined from MRA images.…”
Section: Intracranial Aneurysmmentioning
confidence: 99%