215 citations · 345 across the 14 of their papers we have counts for
8 papers · 1 filter
One-Shot Medical Landmark Detection
Qingsong Yao, Quan Quan, Li Xiao +1
The success of deep learning methods relies on the availability of a large number of datasets with annotations; however, curating such datasets is burdensome, especially for medica…
Incremental Learning for Multi-organ Segmentation with Partially Labeled Datasets
Pengbo Liu, Li Xiao, S. Kevin Zhou
There exists a large number of datasets for organ segmentation, which are partially annotated, and sequentially constructed. A typical dataset is constructed at a certain time by c…
You Only Learn Once: Universal Anatomical Landmark Detection
Heqin Zhu, Qingsong Yao, Li Xiao +1
Detecting anatomical landmarks in medical images plays an essential role in understanding the anatomy and planning automated processing. In recent years, a variety of deep neural n…
Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models
Pengbo Liu, Hu Han, Yuanqi Du +9
Purpose: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing methods for pelvic bone segme…
G-RCN: Optimizing the Gap between Classification and Localization Tasks for Object Detection
Yufan Luo, Li Xiao
Multi-task learning is widely used in computer vision. Currently, object detection models utilize shared feature map to complete classification and localization tasks simultaneousl…
PBRnet: Pyramidal Bounding Box Refinement to Improve Object Localization Accuracy
Li Xiao, Yufan Luo, Chunlong Luo +5
Many recently developed object detectors focused on coarse-to-fine framework which contains several stages that classify and regress proposals from coarse-grain to fine-grain, and…
Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography
Li Xiao, Cheng Zhu, Junjun Liu +3
Deep learning object detection algorithm has been widely used in medical image analysis. Currently all the object detection tasks are based on the data annotated with object classe…
DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks
Li Xiao, Chunlong Luo, Tianqi Yu +6
Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate the enumeration process, we develop a chromosome enumeration framework, DeepACEv2,…