Computer-Aided Diagnosis: Clinical Applications in the Breast

Vomweg, T. W.

doi:10.1007/978-3-540-49830-8_26

Cited by 2 publications

(2 citation statements)

References 177 publications

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“…Recently, CAD systems have been used in clinical routine in the rather mature field of cancer screening in mammograms and allowed to improve the detection of non-palpable cancerous masses [15,38]. Image-based CAD systems are expected to be introduced into clinical routine for several other organs such as the chest, colon, brain, liver, skeletal and vascular systems [1,9,26].…”

Section: Introductionmentioning

confidence: 99%

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows

et al. 2011

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Section: Introductionmentioning

confidence: 99%

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows

et al. 2011

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“…However, it quickly became clear that physicians and radiologists have to take the final decision and the outputs of CAD systems must be used as second opinions and information providers [ 25 ]. Recently, CADe systems have been used in clinical practice in the rather mature field of cancer screening in mammograms and allowed to improve the detection of non–palpable cancerous masses [ 26 ]. Other notable examples are the assisted detection of lung nodules in chest radiographs such as Riverain Medical’s OnGuard 1 which have obtained approval from the United States’ Food and Drug Administration (FDA).…”

Section: Introductionmentioning

confidence: 99%

Prototypes for Content-Based Image Retrieval in Clinical Practice

Depeursinge¹,

Fischer²,

Müller³

et al. 2011

TOMINFOJ

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Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice.We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word “retrieval” in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems.In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently.In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice.

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Computer-Aided Diagnosis: Clinical Applications in the Breast

Cited by 2 publications

References 177 publications

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows

Prototypes for Content-Based Image Retrieval in Clinical Practice

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