Computer-based nodule malignancy risk assessment in thyroid ultrasound imageS

Επιστημονική δημοσίευση - Άρθρο Περιοδικού uoadl:3028229 7 Αναγνώσεις

Μονάδα:
Ερευνητικό υλικό ΕΚΠΑ
Τίτλος:
Computer-based nodule malignancy risk assessment in thyroid ultrasound imageS
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
This paper presents a computer-based approach for detection, delineation, and malignancy risk assessment of thyroid nodules in ultrasound (US) images. The proposed approach is automatic and integrates processes for: the thyroid gland boundaries detection, the detection of nodular lesions within the thyroid gland, the delineation of the detected nodules, and the classification of thyroid nodules according to malignancy risk. These processes embed textural and shape feature vectors derived from the US images, as well as state of-the-art medical image analysis and pattern recognition tools. The obtained classification performance, which is associated with automatic malignancy risk assessment, was evaluated by means of the receiver operating characteristic (ROC), demonstrating an area under curve (AUC) equal to 0.93. The quantification of the results shows that the proposed approach: (1) contributes to the objectification of the diagnostic process by the utilization of explicit image features, whereas it can provide the diagnosticians with a second opinion, (2) is applicable in clinical practice and could contribute to the reduction of false medical decisions.
Έτος δημοσίευσης:
2011
Συγγραφείς:
Legakis, I.
Savelonas, M.A.
Maroulis, D.
Iakovidis, D.K.
Περιοδικό:
International Journal of Computers and Applications
Τόμος:
33
Αριθμός / τεύχος:
1
Σελίδες:
29-35
Λέξεις-κλειδιά:
Classification performance; Clinical practices; Computer-based approach; Computer-based medical approaches; Diagnostic process; Image features; Malignancy risk assessment; Medical decisions; Medical image analysis; Nodular lesions; Receiver operating characteristics; Shape features; Thyroid glands; Thyroid nodule; Thyroid nodules; Ultrasound; Ultrasound images, Feature extraction; Medical imaging; Rating; Ultrasonic applications; Ultrasonics, Risk assessment
Επίσημο URL (Εκδότης):
DOI:
10.2316/Journal.202.2011.1.202-2955
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