Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.
We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype...
| Publicado en: | Journal of Digital Imaging Vol. 30; no. 5; pp. 629 - 640 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=125205803&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 125205803 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Oct2017 vid: 30 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 125205803 125205803 144143959 125205803 10.1007/s10278-017-9968-3 125205803 ppf: 629 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm. aug: au: Nemoto, Mitsutaka Hayashi, Naoto Hanaoka, Shouhei Nomura, Yukihiro Miki, Soichiro Yoshikawa, Takeharu affil: Department of Computational Diagnostic Radiology and Preventive Medicine , The University of Tokyo Hospital , 7-3-1 Hongo, Bunkyo-ku Tokyo 113-8655 Japan sug: subj: Radiographic Image Interpretation, Computer-Assisted Methods Diagnosis, Computer Assisted Systems Design Methods Artificial Intelligence Algorithms Evaluation Research Validation Studies Human ab: We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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