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 …
Computer‐aided diagnosis systems for lung cancer: challenges and methodologies
This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
Artificial intelligence in medicine: What is it doing for us today?
A Becker - Health Policy and Technology, 2019 - Elsevier
With its origins in the mid-to late-1900s, today, artificial intelligence (AI) is used in a wide
range of medical fields for varying purposes. This review first covers the early work …
range of medical fields for varying purposes. This review first covers the early work …
Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning
B van Ginneken - Radiological physics and technology, 2017 - Springer
Half a century ago, the term “computer-aided diagnosis”(CAD) was introduced in the
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …
Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM
The roles of physicists in medical imaging have expanded over the years, from the study of
imaging systems (sources and detectors) and dose to the assessment of image quality and …
imaging systems (sources and detectors) and dose to the assessment of image quality and …
Pulmonary nodule classification with deep convolutional neural networks on computed tomography images
Computer aided detection (CAD) systems can assist radiologists by offering a second
opinion on early diagnosis of lung cancer. Classification and feature representation play …
opinion on early diagnosis of lung cancer. Classification and feature representation play …
Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)
When lung nodules overlap with ribs or clavicles in chest radiographs, it can be difficult for
radiologists as well as computer-aided diagnostic (CAD) schemes to detect these nodules …
radiologists as well as computer-aided diagnostic (CAD) schemes to detect these nodules …
Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network
K Suzuki, F Li, S Sone, K Doi - IEEE transactions on medical …, 2005 - ieeexplore.ieee.org
Low-dose helical computed tomography (LDCT) is being applied as a modality for lung
cancer screening. It may be difficult, however, for radiologists to distinguish malignant from …
cancer screening. It may be difficult, however, for radiologists to distinguish malignant from …
Lung cancer detection on CT images by using image processing
Lung cancer seems to be the common cause of death among people throughout the world.
Early detection of lung cancer can increase the chance of survival among people. The …
Early detection of lung cancer can increase the chance of survival among people. The …
[HTML][HTML] Use of deep learning to detect cardiomegaly on thoracic radiographs in dogs
S Burti, VL Osti, A Zotti, T Banzato - The Veterinary Journal, 2020 - Elsevier
The purpose of this study was to develop a computer-aided detection (CAD) device based
on convolutional neural networks (CNNs) to detect cardiomegaly from plain radiographs in …
on convolutional neural networks (CNNs) to detect cardiomegaly from plain radiographs in …