220 citations · 1.4k across the 42 of their papers we have counts for
14 papers · 1 filter
Edge-aware Feature Aggregation Network for Polyp Segmentation
Tao Zhou, Yizhe Zhang, Geng Chen +3
Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer (CRC) in clinical practice. However, due to scale variation and blurry polyp boundar…
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation
Yizhe Zhang, Tao Zhou, Shuo Wang +3
The Segment Anything Model (SAM) exhibits a capability to segment a wide array of objects in natural images, serving as a versatile perceptual tool for various downstream image seg…
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang +2
Diffusion models have demonstrated excellent potential for generating diverse images. However, their performance often suffers from slow generation due to iterative denoising. Know…
Can SAM Segment Polyps?
Tao Zhou, Yizhe Zhang, Yi Zhou +2
Recently, Meta AI Research releases a general Segment Anything Model (SAM), which has demonstrated promising performance in several segmentation tasks. As we know, polyp segmentati…
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)
Haoran Wang, Yan Zhu, Wenzheng Qin +5
The advance of computer-aided detection systems using deep learning opened a new scope in endoscopic image analysis. However, the learning-based models developed on closed datasets…
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang +2
Diffusion models (DMs) have recently emerged as SoTA tools for generative modeling in various domains. Standard DMs can be viewed as an instantiation of hierarchical variational au…
H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation
Peixian Liang, Yizhe Zhang, Yifan Ding +5
Deep learning (DL) based semantic segmentation methods have achieved excellent performance in biomedical image segmentation, producing high quality probability maps to allow extrac…
Second-order Non-local Attention Networks for Person Re-identification
Bryan, Xia, Yuan Gong +2
Recent efforts have shown promising results for person re-identification by designing part-based architectures to allow a neural network to learn discriminative representations fro…
Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
Peixian Liang, Jianxu Chen, Hao Zheng +3
The Encoder-Decoder architecture is a main stream deep learning model for biomedical image segmentation. The encoder fully compresses the input and generates encoded features, and…
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
Hao Zheng, Yizhe Zhang, Lin Yang +4
3D image segmentation plays an important role in biomedical image analysis. Many 2D and 3D deep learning models have achieved state-of-the-art segmentation performance on 3D biomed…
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation
Lin Yang, Yizhe Zhang, Zhuo Zhao +5
In recent years, deep learning (DL) methods have become powerful tools for biomedical image segmentation. However, high annotation efforts and costs are commonly needed to acquire…
A New Registration Approach for Dynamic Analysis of Calcium Signals in Organs
Peixian Liang, Jianxu Chen, Pavel A. Brodskiy +6
Wing disc pouches of fruit flies are a powerful genetic model for studying physiological intercellular calcium () signals for dynamic analysis of cell signaling in organ d…
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
Lin Yang, Yizhe Zhang, Jianxu Chen +2
Image segmentation is a fundamental problem in biomedical image analysis. Recent advances in deep learning have achieved promising results on many biomedical image segmentation ben…
Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation
Jianxu Chen, Lin Yang, Yizhe Zhang +2
Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation perfor- mance. To exploit…