AIMC Topic:
Ultrasonography
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Deep convolutional neural network models for the diagnosis of thyroid cancer - Authors' reply.
The Lancet. Oncology
Mar 1, 2019
Deep convolutional neural network models for the diagnosis of thyroid cancer.
The Lancet. Oncology
Mar 1, 2019
Deep convolutional neural network models for the diagnosis of thyroid cancer.
The Lancet. Oncology
Mar 1, 2019
Semi-dynamic Control of FCM Initialization for Automatic Extraction of Inflamed Appendix from Ultrasonography.
Current medical imaging reviews
Jan 1, 2019
BACKGROUND: Current naked-eye examination of the ultrasound images for inflamed appendix has limitations due to its intrinsic operator subjectivity problem.
Feasibility of Image Registration for Ultrasound-Guided Prostate Radiotherapy Based on Similarity Measurement by a Convolutional Neural Network.
Technology in cancer research & treatment
Jan 1, 2019
PURPOSE: Registration of 3-dimensional ultrasound images poses a challenge for ultrasound-guided radiation therapy of the prostate since ultrasound image content changes significantly with anatomic motion and ultrasound probe position. The purpose of...
Deep Learning-Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study.
Thyroid : official journal of the American Thyroid Association
Oct 1, 2018
BACKGROUND: The presence of metastatic lymph nodes is a prognostic indicator for patients with thyroid carcinomas and is an important determinant of clinical decision making. However, evaluating neck lymph nodes requires experience and is labor- and ...
Online Robust Projective Dictionary Learning: Shape Modeling for MR-TRUS Registration.
IEEE transactions on medical imaging
Apr 1, 2018
Robust and effective shape prior modeling from a set of training data remains a challenging task, since the shape variation is complicated, and shape models should preserve local details as well as handle shape noises. To address these challenges, a ...
Machine learning for medical ultrasound: status, methods, and future opportunities.
Abdominal radiology (New York)
Apr 1, 2018
Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving t...
The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.
Journal of thrombosis and thrombolysis
Oct 1, 2017
Venous thromboembolism (VTE) is a potentially life-threatening condition that includes both deep vein thrombosis (DVT) and pulmonary embolism. We sought to improve detection and reporting of children with a new diagnosis of VTE by applying natural la...
Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.
Journal of digital imaging
Aug 1, 2017
With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper pre...
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