Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
Overview of deep learning in medical imaging
K Suzuki - Radiological physics and technology, 2017 - Springer
The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …
The contemporary management of cancers of the sinonasal tract in adults
Sinonasal malignancies make up< 5% of all head and neck neoplasms, with an incidence of
0.5–1.0 per 100,000. The outcome of these rare malignancies has been poor, whereas …
0.5–1.0 per 100,000. The outcome of these rare malignancies has been poor, whereas …
Multi-scale convolutional neural networks for lung nodule classification
We investigate the problem of diagnostic lung nodule classification using thoracic Computed
Tomography (CT) screening. Unlike traditional studies primarily relying on nodule …
Tomography (CT) screening. Unlike traditional studies primarily relying on nodule …
Deeplung: Deep 3d dual path nets for automated pulmonary nodule detection and classification
In this work, we present a fully automated lung computed tomography (CT) cancer diagnosis
system, DeepLung. DeepLung consists of two components, nodule detection (identifying the …
system, DeepLung. DeepLung consists of two components, nodule detection (identifying the …
Deep learning for lung Cancer detection and classification
Lung cancer is one of the main reasons for death in the world among both men and women,
with an impressive rate of about five million deadly cases per year. Computed Tomography …
with an impressive rate of about five million deadly cases per year. Computed Tomography …
[HTML][HTML] Imaging and cancer: a review
L Fass - Molecular oncology, 2008 - Elsevier
Multiple biomedical imaging techniques are used in all phases of cancer management.
Imaging forms an essential part of cancer clinical protocols and is able to furnish …
Imaging forms an essential part of cancer clinical protocols and is able to furnish …
Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network
L Wang, S Yang, S Yang, C Zhao, G Tian… - World journal of surgical …, 2019 - Springer
Background In this study, images of 2450 benign thyroid nodules and 2557 malignant
thyroid nodules were collected and labeled, and an automatic image recognition and …
thyroid nodules were collected and labeled, and an automatic image recognition and …
Computer-aided detection (CADe) and diagnosis (CADx) system for lung cancer with likelihood of malignancy
M Firmino, G Angelo, H Morais, MR Dantas… - Biomedical engineering …, 2016 - Springer
Abstract Background CADe and CADx systems for the detection and diagnosis of lung
cancer have been important areas of research in recent decades. However, these areas are …
cancer have been important areas of research in recent decades. However, these areas are …
Predicting women with depressive symptoms postpartum with machine learning methods
Postpartum depression (PPD) is a detrimental health condition that affects 12% of new
mothers. Despite negative effects on mothers' and children's health, many women do not …
mothers. Despite negative effects on mothers' and children's health, many women do not …