Neuron tracing from light microscopy images: automation, deep learning and bench testing
Motivation Large-scale neuronal morphologies are essential to neuronal typing, connectivity
characterization and brain modeling. It is widely accepted that automation is critical to the …
characterization and brain modeling. It is widely accepted that automation is critical to the …
[HTML][HTML] Human treelike tubular structure segmentation: A comprehensive review and future perspectives
Various structures in human physiology follow a treelike morphology, which often expresses
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
RTNet: relation transformer network for diabetic retinopathy multi-lesion segmentation
Automatic diabetic retinopathy (DR) lesions segmentation makes great sense of assisting
ophthalmologists in diagnosis. Although many researches have been conducted on this …
ophthalmologists in diagnosis. Although many researches have been conducted on this …
Common limitations of image processing metrics: A picture story
While the importance of automatic image analysis is continuously increasing, recent meta-
research revealed major flaws with respect to algorithm validation. Performance metrics are …
research revealed major flaws with respect to algorithm validation. Performance metrics are …
Directional connectivity-based segmentation of medical images
Anatomical consistency in biomarker segmentation is crucial for many medical image
analysis tasks. A promising paradigm for achieving anatomically consistent segmentation …
analysis tasks. A promising paradigm for achieving anatomically consistent segmentation …
Global transformer and dual local attention network via deep-shallow hierarchical feature fusion for retinal vessel segmentation
Clinically, retinal vessel segmentation is a significant step in the diagnosis of fundus
diseases. However, recent methods generally neglect the difference of semantic information …
diseases. However, recent methods generally neglect the difference of semantic information …
An automatic multi-tissue human fetal brain segmentation benchmark using the fetal tissue annotation dataset
It is critical to quantitatively analyse the developing human fetal brain in order to fully
understand neurodevelopment in both normal fetuses and those with congenital disorders …
understand neurodevelopment in both normal fetuses and those with congenital disorders …
High-level prior-based loss functions for medical image segmentation: A survey
Today, deep convolutional neural networks (CNNs) have demonstrated state of the art
performance for supervised medical image segmentation, across various imaging modalities …
performance for supervised medical image segmentation, across various imaging modalities …
Relationformer: A Unified Framework for Image-to-Graph Generation
A comprehensive representation of an image requires understanding objects and their
mutual relationship, especially in image-to-graph generation, eg, road network extraction …
mutual relationship, especially in image-to-graph generation, eg, road network extraction …
Multi-site, multi-domain airway tree modeling
Open international challenges are becoming the de facto standard for assessing computer
vision and image analysis algorithms. In recent years, new methods have extended the …
vision and image analysis algorithms. In recent years, new methods have extended the …