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01-08-2016 | Images in Obstetrics and Gynecology

LECANDUS study (LEsion CANdidate Detection in UltraSound Data): evaluation of image analysis algorithms for breast lesion detection in volume ultrasound data

Authors: Michael Golatta, Désirée Zeegers, Konstantinos Filippatos, Leah-Larissa Binder, Alexander Scharf, Geraldine Rauch, Joachim Rom, Florian Schütz, Christof Sohn, Joerg Heil

Published in: Archives of Gynecology and Obstetrics | Issue 2/2016

Abstract

Purpose

This study aims at developing and evaluating a prototype of a lesion candidate detection algorithm for a 3D-US computer-aided diagnosis (CAD) system.

Methods

Additionally, to routine imaging, automated breast volume scans (ABVS) were performed on 63 patients. All ABVS exams were analyzed and annotated before the evaluation with different algorithm blob detectors characterized by different blob-radiuses, voxel-sizes and the quantiles of blob filter responses to find lesion candidates. Lesions found in candidates were compared to the prior annotations.

Results

All histologically proven lesions were detected with at least one algorithm. The algorithm with optimal sensitivity detected all cancers (sensitivity = 100 %) with a very low positive predictive value due to a high false-positive rate.

Conclusions

ABVS is a new technology which can be analyzed by a CAD software. Using different algorithms, lesions can be detected with a very high and accurate sensitivity. Further research for feature extraction and lesion classification is needed aiming at reducing the false-positive hits.

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Title: LECANDUS study (LEsion CANdidate Detection in UltraSound Data): evaluation of image analysis algorithms for breast lesion detection in volume ultrasound data
Authors: Michael Golatta
Désirée Zeegers
Konstantinos Filippatos
Leah-Larissa Binder
Alexander Scharf
Geraldine Rauch
Joachim Rom
Florian Schütz
Christof Sohn
Joerg Heil
Publication date: 01-08-2016
Publisher: Springer Berlin Heidelberg
Published in: Archives of Gynecology and Obstetrics / Issue 2/2016
Print ISSN: 0932-0067
Electronic ISSN: 1432-0711
DOI: https://doi.org/10.1007/s00404-016-4127-5

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LECANDUS study (LEsion CANdidate Detection in UltraSound Data): evaluation of image analysis algorithms for breast lesion detection in volume ultrasound data

Abstract

Purpose

Methods

Results

Conclusions

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Abstract

Purpose

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Results

Conclusions

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