130 citations · 255 across the 10 of their papers we have counts for
10 papers
Push the Boundary of SAM: A Pseudo-label Correction Framework for Medical Segmentation
Ziyi Huang, Hongshan Liu, Haofeng Zhang +7
Segment anything model (SAM) has emerged as the leading approach for zero-shot learning in segmentation tasks, offering the advantage of avoiding pixel-wise annotations. It is part…
Self-paced Resistance Learning against Overfitting on Noisy Labels
Xiaoshuang Shi, Zhenhua Guo, Kang Li +2
Noisy labels composed of correct and corrupted ones are pervasive in practice. They might significantly deteriorate the performance of convolutional neural networks (CNNs), because…
Cluster Activation Mapping with Applications to Medical Imaging
Sarah Ryan, Nichole Carlson, Harris Butler +3
An open question in deep clustering is how to understand what in the image is creating the cluster assignments. This visual understanding is essential to be able to trust the resul…
A Scalable Optimization Mechanism for Pairwise based Discrete Hashing
Xiaoshuang Shi, Fuyong Xing, Zizhao Zhang +3
Maintaining the pair similarity relationship among originally high-dimensional data into a low-dimensional binary space is a popular strategy to learn binary codes. One simiple and…
Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning
Jinzheng Cai, Le Lu, Fuyong Xing +1
Automatic pancreas segmentation in radiology images, eg., computed tomography (CT) and magnetic resonance imaging (MRI), is frequently required by computer-aided screening, diagnos…
Recent Advances in the Applications of Convolutional Neural Networks to Medical Image Contour Detection
Zizhao Zhang, Fuyong Xing, Hai Su +2
The fast growing deep learning technologies have become the main solution of many machine learning problems for medical image analysis. Deep convolution neural networks (CNNs), as…
Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function
Jinzheng Cai, Le Lu, Yuanpu Xie +2
Deep neural networks have demonstrated very promising performance on accurate segmentation of challenging organs (e.g., pancreas) in abdominal CT and MRI scans. The current deep le…
MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network
Zizhao Zhang, Yuanpu Xie, Fuyong Xing +2
The inability to interpret the model prediction in semantically and visually meaningful ways is a well-known shortcoming of most existing computer-aided diagnosis methods. In this…
Revisiting Graph Construction for Fast Image Segmentation
Zizhao Zhang, Fuyong Xing, Hanzi Wang +4
In this paper, we propose a simple but effective method for fast image segmentation. We re-examine the locality-preserving character of spectral clustering by constructing a graph…
SemiContour: A Semi-supervised Learning Approach for Contour Detection
Zizhao Zhang, Fuyong Xing, Xiaoshuang Shi +1
Supervised contour detection methods usually require many labeled training images to obtain satisfactory performance. However, a large set of annotated data might be unavailable or…