Evaluation of functional MRI-based human brain parcellation: a review
Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can
significantly affect the outcome of the analysis. In recent years, several novel approaches for …
significantly affect the outcome of the analysis. In recent years, several novel approaches for …
FMRNet: A fused network of multiple tumoral regions for breast tumor classification with ultrasound images
Purpose Recent studies have illustrated that the peritumoral regions of medical images have
value for clinical diagnosis. However, the existing approaches using peritumoral regions …
value for clinical diagnosis. However, the existing approaches using peritumoral regions …
GraphXCOVID: explainable deep graph diffusion pseudo-labelling for identifying COVID-19 on chest X-rays
AI Aviles-Rivero, P Sellars, CB Schönlieb… - Pattern Recognition, 2022 - Elsevier
Can one learn to diagnose COVID-19 under extreme minimal supervision? Since the
outbreak of the novel COVID-19 there has been a rush for developing automatic techniques …
outbreak of the novel COVID-19 there has been a rush for developing automatic techniques …
Dynamic ensemble learning with multi-view kernel collaborative subspace clustering for hyperspectral image classification
Recently, a series of collaborative representation (CR) methods have attracted much
attention for hyperspectral images classification. In this article, two CR-based dynamic …
attention for hyperspectral images classification. In this article, two CR-based dynamic …
Integrating multimodal and longitudinal neuroimaging data with multi-source network representation learning
Uncovering the complex network of the brain is of great interest to the field of neuroimaging.
Mining from these rich datasets, scientists try to unveil the fundamental biological …
Mining from these rich datasets, scientists try to unveil the fundamental biological …