activity
20182026
most citedBoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation

32 citations · 61 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2026

TopoCL: Topological Contrastive Learning for Medical Imaging

Guangyu Meng, Pengfei Gu, Peixian Liang +3

Contrastive learning (CL) has become a powerful approach for learning representations from unlabeled images. However, existing CL methods focus predominantly on visual appearance f…

cs.CV2025

Cell Instance Segmentation: The Devil Is in the Boundaries

Peixian Liang, Yifan Ding, Yizhe Zhang +9

State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from b…

cs.CV2024

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

Nishchal Sapkota, Yejia Zhang, Sirui Li +7

Male infertility accounts for about one-third of global infertility cases. Manual assessment of sperm abnormalities through head morphology analysis encounters issues of observer v…

cs.CV2024★ 1 cited

Efficient approximation of Earth Mover's Distance Based on Nearest Neighbor Search

Guangyu Meng, Ruyu Zhou, Liu Liu +5

Earth Mover's Distance (EMD) is an important similarity measure between two distributions, used in computer vision and many other application domains. However, its exact calculatio…

cs.CV2023★ 10 cited

Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model

Yizhe Zhang, Tao Zhou, Shuo Wang +2

The Segment Anything Model (SAM) is a recently developed large model for general-purpose segmentation for computer vision tasks. SAM was trained using 11 million images with over 1…

cs.CV2022

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

Yejia Zhang, Pengfei Gu, Nishchal Sapkota +3

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 le…

eess.IV2022

Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models

Yizhe Zhang, Suraj Mishra, Peixian Liang +2

We aim to quantitatively measure the practical usability of medical image segmentation models: to what extent, how often, and on which samples a model's predictions can be used/tru…

cs.CV2022

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…

cs.CV2019★ 2 cited

SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation

Yizhe Zhang, Lin Yang, Hao Zheng +5

Supervised training a deep neural network aims to "teach" the network to mimic human visual perception that is represented by image-and-label pairs in the training data. Superpixel…

cs.CV2019★ 2 cited

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…

cs.CV2019

CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentation

Suraj Mishra, Peixian Liang, Adam Czajka +2

Convolutional neural networks (CNNs) for biomedical image analysis are often of very large size, resulting in high memory requirement and high latency of operations. Searching for…

cs.CV2018★ 12 cited

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…

cs.CV2018★ 32 cited

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…

cs.CV2018★ 2 cited

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…