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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

15.03.2018 | Original Article

Fully automatic detection of renal cysts in abdominal CT scans

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 7/2018

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Abstract

Purpose

Simple renal cysts are a common benign finding in abdominal CT scans. However, since they may evolve in time, simple cysts need to be reported. With an ever-growing number of slices per CT scan, cysts are easily overlooked by the overloaded radiologist. In this paper, we address the detection of simple renal cysts as an incidental finding in a real clinical setting.

Methods

We propose a fully automatic framework for renal cyst detection, supported by a robust segmentation of the kidneys performed by a fully convolutional neural network. A combined 3D distance map of the kidneys and surrounding fluids provides initial candidates for cysts. Eventually, a second convolutional neural network classifies the candidates as cysts or non-cyst objects.

Results

Performance was evaluated on 52 abdominal CT scans selected at random in a real radiological workflow and containing over 70 cysts annotated by an experienced radiologist. Setting the minimal cyst diameter to 10 mm, the algorithm detected 59/70 cysts (true-positive rate = 84.3%) while producing an average of 1.6 false-positive per case.

Conclusions

The obtained results suggest the proposed framework is a promising approach for the automatic detection of renal cysts as incidental findings of abdominal CT scans.

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Titel: Fully automatic detection of renal cysts in abdominal CT scans
Publikationsdatum: 15.03.2018
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 7/2018
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-018-1726-6

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Fully automatic detection of renal cysts in abdominal CT scans

Abstract

Purpose

Methods

Results

Conclusions

Neu im Fachgebiet Radiologie

Fünf Dinge, die im Kindernotfall besser zu unterlassen sind

Wie toxische Männlichkeit der Gesundheit von Männern schadet

Studie bestätigt Potenzial von KI in der Radiologie

Quantitative Angiografie könnte IVUS-Alternative darstellen

Update Radiologie

Live-Webinar: Aktuelle Leitlinien bei Herz-Kreislauf-Erkrankungen

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusions

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