Search Results for author: Yejia Zhang

Found 10 papers, 2 papers with code

SHMC-Net: A Mask-guided Feature Fusion Network for Sperm Head Morphology Classification

1 code implementation6 Feb 2024 Nishchal Sapkota, Yejia Zhang, Sirui Li, Peixian Liang, Zhuo Zhao, Jingjing Zhang, Xiaomin Zha, Yiru Zhou, Yunxia Cao, Danny Z Chen

We propose a new approach for sperm head morphology classification, called SHMC-Net, which uses segmentation masks of sperm heads to guide the morphology classification of sperm images.

Morphology classification

RR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification

no code implementations9 Sep 2023 Yizhe Zhang, Shuo Wang, Yejia Zhang, Danny Z. Chen

Conformal prediction (CP) generates a set of predictions for a given test sample such that the prediction set almost always contains the true label (e. g., 99. 5\% of the time).

Conformal Prediction Decision Making +2

SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings

1 code implementation23 Jul 2023 Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Danny Z. Chen

Modern medical image segmentation methods primarily use discrete representations in the form of rasterized masks to learn features and generate predictions.

3D Shape Reconstruction Image Segmentation +4

ConvFormer: Combining CNN and Transformer for Medical Image Segmentation

no code implementations15 Nov 2022 Pengfei Gu, Yejia Zhang, Chaoli Wang, Danny Z. Chen

(2) A residual-shaped hybrid stem based on a combination of convolutions and Enhanced DeTrans is developed to capture both local and global representations to enhance representation ability.

Image Segmentation Medical Image Segmentation +2

Unsupervised Feature Clustering Improves Contrastive Representation Learning for Medical Image Segmentation

no code implementations15 Nov 2022 Yejia Zhang, Xinrong Hu, Nishchal Sapkota, Yiyu Shi, Danny Z. Chen

Self-supervised instance discrimination is an effective contrastive pretext task to learn feature representations and address limited medical image annotations.

Clustering Contrastive Learning +4

A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning

no code implementations15 Nov 2022 Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Hao Zheng, Peixian Liang, Danny Z. Chen

High annotation costs and limited labels for dense 3D medical imaging tasks have recently motivated an assortment of 3D self-supervised pretraining methods that improve transfer learning performance.

Image Segmentation Medical Image Segmentation +3

A New Registration Approach for Dynamic Analysis of Calcium Signals in Organs

no code implementations1 Feb 2018 Peixian Liang, Jianxu Chen, Pavel A. Brodskiy, Qinfeng Wu, Yejia Zhang, Yizhe Zhang, Lin Yang, Jeremiah J. Zartman, Danny Z. Chen

A key to analyzing spatial-temporal patterns of $Ca^{2+}$ signal waves is to accurately align the pouches across image sequences.

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