Computer-Aided Diagnosis of Thyroid Nodule: A Review

Abstract

ABSTRACT

Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images

“…6 These have led to extensive research in developing semi-automatically or automatically effective ultrasound image analysis techniques called computer aided detection (CAD) methods so as to obtain accurate, reproducible and more objective detection results. [7][8][9][10][11] The conventional CAD methods typically rely on the same three-step procedure: [12][13][14][15] (a) image pre-processing including denoising, enhancement, segmentation and so on; 16,17 (b) extracting and selecting the visual and effective features can represent major appearance components of the thyroid nodules; (c) detection by a classifier. Tsantis et al 7 utilized various morphological and wavelet-based features toward malignancy risk evaluation of thyroid nodules based on support vector machines (SVMs) and probabilistic neural networks (PNNs).…”

Comparative assessment of texture features for the identification of cancer in ultrasound images: a review

“…The thyroid gland, which is located in front of the neck, secretes hormones that influence protein synthesis and the metabolic rate [27]. US imaging is often used to diagnose thyroid nodules which are typically characterized as hypo-, iso-, or hyperechoic [28]. Thyroid nodules are typically heterogeneous with various internal components, demonstrating how texture analysis can be a powerful tool in identifying cancer in thyroid US images.…”

Kesesuaian Pemeriksaan Ultrasonografi dan Computer-Aided Diagnosis tentang Fitur Posterior dan Batas Lesi dalam Menentukan Nodul Jinak dan Ganas Payudara

“…10 CAD bekerja berdasarkan teknik pengolahan citra dan pengenalan pola, meliputi pra-pengolahan, segmentasi, penggalian ciri dan klasifikasi. 16 Sistem CAD kanker payudara yang diusulkan pada penelitian ini berdasarkan klasifikasi ciri batas dan fitur posterior. Tahap awal pra-pengolahan dilakukan pemilihan area gambar USG yang mengandung lesi (region of interest atau ROI).…”