Int J Comput Assist Radiol Surg - Computer-aided focal liver lesion detection.

Tópicos

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Resumo

RPOSE: Our aim is to develop an automatic method which can detect diverse focal liver lesions (FLLs) in 3D CT volumes.METHOD: A hybrid generative-discriminative framework is proposed. It first uses a generative model to describe non-lesion components and then identifies all candidate FLLs within a 3D liver volume by eliminating non-lesion components. It subsequently uses a discriminative approach to suppress false positives with the advantage of tumoroid, a novel measurement combining three shape features spherical symmetry, compactness and size.RESULTS: This method was tested on 71 abdominal CT datasets (5,854 slices from 61 patients, with 261 FLLs covering six pathological types) and evaluated using the free-response receiver operating characteristic (FROC) curves. Overall, it achieved a true positive rate of 90 % with one false positive per liver. It degenerated gently with the decrease in lesion sizes to 30 ml. It achieved a true-positive rate of 36 % when tested on the lesions less than 4 ml. The average computing time of the lesion detection is 4 min and 28 s per CT volume on a PC with 2.67 GHz CPU and 4.0 GB RAM.CONCLUSIONS: The proposed method is comparable to the radiologists' visual investigation in terms of efficiency. The tool has great potential to reduce radiologists' burden in going through thousands of images routinely.

Resumo Limpo

rpose aim develop automat method can detect divers focal liver lesion flls d ct volumesmethod hybrid generativediscrimin framework propos first use generat model describ nonles compon identifi candid flls within d liver volum elimin nonles compon subsequ use discrimin approach suppress fals posit advantag tumoroid novel measur combin three shape featur spheric symmetri compact sizeresult method test abdomin ct dataset slice patient flls cover six patholog type evalu use freerespons receiv oper characterist froc curv overal achiev true posit rate one fals posit per liver degener gentl decreas lesion size ml achiev trueposit rate test lesion less ml averag comput time lesion detect min s per ct volum pc ghz cpu gb ramconclus propos method compar radiologist visual investig term effici tool great potenti reduc radiologist burden go thousand imag routin

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