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CHMELÍK, J. JAKUBÍČEK, R. JAN, J. OUŘEDNÍČEK, P. LAMBERT, L. AMADORI, E. GAVELLI, G.
Original Title
Fully Automatic CAD System for Segmentation and Classification of Spinal Metastatic Lesions in CT Data
Type
conference paper
Language
English
Original Abstract
Our contribution presents a research progress in our long-term project that deals with spine analysis in computed tomography (CT) data. A fully automatic computer-aided diagnosis (CAD) system is presented, enabling the simultaneous segmentation and classification of metastatic tissues that can occur in the vertebrae of oncological patients. The task of the proposed CAD system is to segment metastatic lesions and classify them into two categories: osteolytic and osteoblastic. These lesions, especially osteolytic, are ill defined and it is difficult to detect them directly with only information about voxel intensity. The use of several local texture and shape features turned out to be useful for correct classification, however the exact determination of relevant image features is a difficult task. For this reason, the feature determination has been solved by automatic feature extraction provided by a deep convolutional neural network (CNN). The achieved mean sensitivity of detected lesions is greater than 92% with approximately three false positive detections per lesion for both types.
Keywords
CAD; Convolution neural network; Spine analysis; Metastasis; CT data
Authors
CHMELÍK, J.; JAKUBÍČEK, R.; JAN, J.; OUŘEDNÍČEK, P.; LAMBERT, L.; AMADORI, E.; GAVELLI, G.
Released
2. 1. 2019
Publisher
Springer
Location
Singapore
ISBN
978-981-10-9034-9
Book
World Congress on Medical Physics and Biomedical Engineering 2018
1680-0737
Periodical
IFMBE PROCEEDINGS
Year of study
68
Number
1
State
Kingdom of Sweden
Pages from
155
Pages to
158
Pages count
4
URL
https://doi.org/10.1007/978-981-10-9035-6_28
BibTex
@inproceedings{BUT147831, author="CHMELÍK, J. and JAKUBÍČEK, R. and JAN, J. and OUŘEDNÍČEK, P. and LAMBERT, L. and AMADORI, E. and GAVELLI, G.", title="Fully Automatic CAD System for Segmentation and Classification of Spinal Metastatic Lesions in CT Data", booktitle="World Congress on Medical Physics and Biomedical Engineering 2018", year="2019", journal="IFMBE PROCEEDINGS", volume="68", number="1", pages="155--158", publisher="Springer", address="Singapore", doi="10.1007/978-981-10-9035-6\{_}28", isbn="978-981-10-9034-9", issn="1680-0737", url="https://doi.org/10.1007/978-981-10-9035-6_28" }