Simcvd: Simple contrastive voxel-wise representation distillation for semi-supervised medical image segmentation
Automated segmentation in medical image analysis is a challenging task that requires a
large amount of manually labeled data. However, most existing learning-based approaches …
large amount of manually labeled data. However, most existing learning-based approaches …
Convex optimization algorithms in medical image reconstruction—in the age of AI
The past decade has seen the rapid growth of model based image reconstruction (MBIR)
algorithms, which are often applications or adaptations of convex optimization algorithms …
algorithms, which are often applications or adaptations of convex optimization algorithms …
Assessing the ability of generative adversarial networks to learn canonical medical image statistics
In recent years, generative adversarial networks (GANs) have gained tremendous popularity
for potential applications in medical imaging, such as medical image synthesis, restoration …
for potential applications in medical imaging, such as medical image synthesis, restoration …
Need for objective task‐based evaluation of deep learning‐based denoising methods: a study in the context of myocardial perfusion SPECT
Background Artificial intelligence‐based methods have generated substantial interest in
nuclear medicine. An area of significant interest has been the use of deep‐learning (DL) …
nuclear medicine. An area of significant interest has been the use of deep‐learning (DL) …
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
Recent advancements in AI applications to healthcare have shown incredible promise in
surpassing human performance in diagnosis and disease prognosis. With the increasing …
surpassing human performance in diagnosis and disease prognosis. With the increasing …
Learned full waveform inversion incorporating task information for ultrasound computed tomography
Ultrasound computed tomography (USCT) is an emerging imaging modality that holds great
promise for breast imaging. Full-waveform inversion (FWI)-based image reconstruction …
promise for breast imaging. Full-waveform inversion (FWI)-based image reconstruction …
Deep learning approach for the detection of noise type in ancient images
Recent innovations in digital image capturing techniques facilitate the capture of stationary
and moving objects. The images can be easily captured via high-end digital cameras …
and moving objects. The images can be easily captured via high-end digital cameras …
Impact of deep learning-based image super-resolution on binary signal detection
Purpose: Deep learning-based image super-resolution (DL-SR) has shown great promise in
medical imaging applications. To date, most of the proposed methods for DL-SR have only …
medical imaging applications. To date, most of the proposed methods for DL-SR have only …
A deep weakly semi-supervised framework for endoscopic lesion segmentation
In the field of medical image analysis, accurate lesion segmentation is beneficial for the
subsequent clinical diagnosis and treatment planning. Currently, various deep learning …
subsequent clinical diagnosis and treatment planning. Currently, various deep learning …
Adversarial distortion learning for medical image denoising
We present a novel adversarial distortion learning (ADL) for denoising two-and three-
dimensional (2D/3D) biomedical image data. The proposed ADL consists of two auto …
dimensional (2D/3D) biomedical image data. The proposed ADL consists of two auto …