416 citations · 2.7k across the 106 of their papers we have counts for
18 papers · 1 filter
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
Shu Zhang, Jincheng Xu, Yu-Chun Chen +4
Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D conte…
Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction
Jiafa He, Chengwei Pan, Can Yang +4
Automatic blood vessel extraction from 3D medical images is crucial for vascular disease diagnoses. Existing methods based on convolutional neural networks (CNNs) may suffer from d…
Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding
Liyan Sun, Chenxin Li, Xinghao Ding +3
Despite deep convolutional neural networks achieved impressive progress in medical image computing and analysis, its paradigm of supervised learning demands a large number of annot…
Adaptive noise imitation for image denoising
Huangxing Lin, Yihong Zhuang, Yue Huang +4
The effectiveness of existing denoising algorithms typically relies on accurate pre-defined noise statistics or plenty of paired data, which limits their practicality. In this work…
A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed Supervision
Liyan Sun, Jianxiong Wu, Xinghao Ding +3
Standard segmentation of medical images based on full-supervised convolutional networks demands accurate dense annotations. Such learning framework is built on laborious manual ann…
The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results
Jie Lian, Jingyu Liu, Yizhou Yu +9
The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab. The challenge is divided into two rounds. In this paper, we present the results of 6 teams wh…
Contralaterally Enhanced Networks for Thoracic Disease Detection
Gangming Zhao, Chaowei Fang, Guanbin Li +2
Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapp…
Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation
Yicheng Wu, Chengwei Pan, Shuqi Wang +3
Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases. Although being ext…
Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification
Chu-ran Wang, Jing Li, Fandong Zhang +4
Mammogram benign or malignant classification with only image-level labels is challenging due to the absence of lesion annotations. Motivated by the symmetric prior that the lesions…
Online Alternate Generator against Adversarial Attacks
Haofeng Li, Yirui Zeng, Guanbin Li +2
The field of computer vision has witnessed phenomenal progress in recent years partially due to the development of deep convolutional neural networks. However, deep learning models…
Generator Versus Segmentor: Pseudo-healthy Synthesis
Zhang Yunlong, Li Chenxin, Lin Xin +6
This paper investigates the problem of pseudo-healthy synthesis that is defined as synthesizing a subject-specific pathology-free image from a pathological one. Recent approaches b…
Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation
Shen Wang, Kongming Liang, Yiming Li +2
Brain midline delineation can facilitate the clinical evaluation of brain midline shift, which plays an important role in the diagnosis and prognosis of various brain pathology. Ne…
ChestX-Det10: Chest X-ray Dataset on Detection of Thoracic Abnormalities
Jingyu Liu, Jie Lian, Yizhou Yu
Instance level detection of thoracic diseases or abnormalities are crucial for automatic diagnosis in chest X-ray images. Most existing works on chest X-rays focus on disease class…
Graph-Structured Referring Expression Reasoning in The Wild
Sibei Yang, Guanbin Li, Yizhou Yu
Grounding referring expressions aims to locate in an image an object referred to by a natural language expression. The linguistic structure of a referring expression provides a lay…
When Relation Networks meet GANs: Relation GANs with Triplet Loss
Runmin Wu, Kunyao Zhang, Lijun Wang +4
Though recent research has achieved remarkable progress in generating realistic images with generative adversarial networks (GANs), the lack of training stability is still a linger…
Kernel Quantization for Efficient Network Compression
Zhongzhi Yu, Yemin Shi, Tiejun Huang +1
This paper presents a novel network compression framework Kernel Quantization (KQ), targeting to efficiently convert any pre-trained full-precision convolutional neural network (CN…
Segmentation-based Method combined with Dynamic Programming for Brain Midline Delineation
Shen Wang, Kongming Liang, Chengwei Pan +5
The midline related pathological image features are crucial for evaluating the severity of brain compression caused by stroke or traumatic brain injury (TBI). The automated midline…
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread
Haofeng Li, Guanbin Li, Binbin Yang +3
Recently deep convolutional neural networks have achieved significant success in salient object detection. However, existing state-of-the-art methods require high-end GPUs to achie…