A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
[HTML][HTML] Impact of quality, type and volume of data used by deep learning models in the analysis of medical images
AR Luca, TF Ursuleanu, L Gheorghe… - Informatics in Medicine …, 2022 - Elsevier
The need for time and attention given by the doctor to the patient, due to the increased
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
Deep learning for biomedical image reconstruction: A survey
Medical imaging is an invaluable resource in medicine as it enables to peer inside the
human body and provides scientists and physicians with a wealth of information …
human body and provides scientists and physicians with a wealth of information …
Fusion deep learning approach combining diffuse optical tomography and ultrasound for improving breast cancer classification
Diffuse optical tomography (DOT) is a promising technique that provides functional
information related to tumor angiogenesis. However, reconstructing the DOT function map of …
information related to tumor angiogenesis. However, reconstructing the DOT function map of …
Tutorial on the use of deep learning in diffuse optical tomography
GM Balasubramaniam, B Wiesel, N Biton, R Kumar… - Electronics, 2022 - mdpi.com
Diffuse optical tomography using deep learning is an emerging technology that has found
impressive medical diagnostic applications. However, creating an optical imaging system …
impressive medical diagnostic applications. However, creating an optical imaging system …
Computational medical image reconstruction techniques: a comprehensive review
Medical image reconstruction (MIR) is the elementary way of producing an internal 3D view
of the patient. MIR is inherently ill-posed, and various approaches have been proposed to …
of the patient. MIR is inherently ill-posed, and various approaches have been proposed to …
Multitask deep learning reconstruction and localization of lesions in limited angle diffuse optical tomography
Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to
assess its optical properties and identify abnormalities. DOT image reconstruction is an ill …
assess its optical properties and identify abnormalities. DOT image reconstruction is an ill …
Reconstruction and localization of tumors in breast optical imaging via convolution neural network based on batch normalization layers
N Murad, MC Pan, YF Hsu - IEEE Access, 2022 - ieeexplore.ieee.org
The Near-Infrared (NIR) Diffuse Optical Tomography (DOT) aims to reconstruct optical-
property images of tissue and identify and localize breast tumors. This study has developed …
property images of tissue and identify and localize breast tumors. This study has developed …
Deep learning application for analyzing of constituents and their correlations in the interpretations of medical images
The need for time and attention, given by the doctor to the patient, due to the increased
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
volume of medical data to be interpreted and filtered for diagnostic and therapeutic purposes …
Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall
Significance: In general, image reconstruction methods used in diffuse optical tomography
(DOT) are based on diffusion approximation, and they consider the breast tissue as a …
(DOT) are based on diffusion approximation, and they consider the breast tissue as a …