Brain MR image classification using superpixel-based deep transfer learning
Nowadays, brain MR (Magnetic Resonance) images are widely used by clinicians to
examine the brain's anatomy to look into various pathological conditions like …
examine the brain's anatomy to look into various pathological conditions like …
One-shot active learning for image segmentation via contrastive learning and diversity-based sampling
Image segmentation tasks based on deep learning usually require a large number of
labeled samples to obtain great performance of Convolutional Neural Networks (CNNs) …
labeled samples to obtain great performance of Convolutional Neural Networks (CNNs) …
Multi-modality fusion & inductive knowledge transfer underlying non-sparse multi-kernel learning and distribution adaption
With the development of sensors, more and more multimodal data are accumulated,
especially in biomedical and bioinformatics fields. Therefore, multimodal data analysis …
especially in biomedical and bioinformatics fields. Therefore, multimodal data analysis …
High-density electroencephalography and speech signal based deep framework for clinical depression diagnosis
Depression is a mental disorder characterized by persistent depressed mood or loss of
interest in performing activities, causing significant impairment in daily routine. Possible …
interest in performing activities, causing significant impairment in daily routine. Possible …
Normal assisted pixel-visibility learning with cost aggregation for multiview stereo
Multiple-View Stereo (MVS) aims to reconstruct the dense 3D representations of scenes.
MVS has potential applications in the fields of autonomous driving (unstructured …
MVS has potential applications in the fields of autonomous driving (unstructured …
[HTML][HTML] Two-Stage Deep Neural Network via Ensemble Learning for Melanoma Classification
Melanoma is a skin disease with a high fatality rate. Early diagnosis of melanoma can
effectively increase the survival rate of patients. There are three types of dermoscopy …
effectively increase the survival rate of patients. There are three types of dermoscopy …
Multimodal-boost: Multimodal medical image super-resolution using multi-attention network with wavelet transform
Multimodal medical images are widely used by clinicians and physicians to analyze and
retrieve complementary information from high-resolution images in a non-invasive manner …
retrieve complementary information from high-resolution images in a non-invasive manner …
[HTML][HTML] Classification of diabetic foot ulcers using class knowledge banks
Y Xu, K Han, Y Zhou, J Wu, X Xie… - … in Bioengineering and …, 2022 - frontiersin.org
Diabetic foot ulcers (DFUs) are one of the most common complications of diabetes.
Identifying the presence of infection and ischemia in DFU is important for ulcer examination …
Identifying the presence of infection and ischemia in DFU is important for ulcer examination …
Detecting depression with heterogeneous graph neural network in clinical interview transcript
Depression has an intense impact on individuals, yet many cases go undiagnosed. Thus, it
is imperative to design an effective model for the automated diagnosis of depression …
is imperative to design an effective model for the automated diagnosis of depression …
KGA: integrating KPCA and GAN for microbial data augmentation
The data used for microbial-based disease diagnosis are characterized by small sample
sizes, imbalanced categories, high dimensionality, and strong sparsity. They pose …
sizes, imbalanced categories, high dimensionality, and strong sparsity. They pose …