Impressive performance on point cloud semantic segmentation has been ach...
We present a novel methodology that combines graph and dense segmentatio...
X-ray coronary angiography (XCA) is used to assess coronary artery disea...
Accurate tooth volume segmentation is a prerequisite for computer-aided
...
In this paper, we introduce an unsupervised cancer segmentation framewor...
3D tooth segmentation is a prerequisite for computer-aided dental diagno...
In video coding, in-loop filters are applied on reconstructed video fram...
Accurate segmentation is a crucial step in medical image analysis and
ap...
To achieve an accurate assessment of root canal therapy, a fundamental s...
Cancer segmentation in whole-slide images is a fundamental step for viab...
The classification of histopathological images is of great value in both...
The detection of nuclei and cells in histology images is of great value ...
Objective: Accurate evaluation of the root canal filling result in X-ray...
As the most economical and routine auxiliary examination in the diagnosi...
In recent years, single modality based gait recognition has been extensi...
Underwater image enhancement, as a pre-processing step to improve the
ac...
Brain tumor segmentation is a challenging problem in medical image analy...
Automated segmentation of brain tumors in 3D magnetic resonance imaging ...
Depression is one of the most common mental health disorders, and a larg...
We present a novel neural network architecture, US-Net, for robust nucle...
Histopathological cancer diagnosis is based on visual examination of sta...
Registration of 3D human body has been a challenging research topic for ...
In this paper, we propose a compact network called CUNet (compact
unsupe...
This paper describes an effective and efficient image classification
fra...
This paper proposes a classification network to image semantic retrieval...