SpindlesTracker: An Automatic and Low-Cost Labeled Workflow for Spindle Analysis-Reference-Cited by-同舟云学术

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SpindlesTracker: An Automatic and Low-Cost Labeled Workflow for Spindle Analysis

Published:2023-08 Issue:8 Volume:27 Page:4098-4109
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Li Zhongzhong¹^ORCID,Jian Yanze²^ORCID,Hu Jiatong¹,Zhang Chuanmin¹,Meng Xuechun¹^ORCID,Liu Ji¹^ORCID

Affiliation:

1. Department of Endocrinology, the First Affiliated Hospital, the National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, School of Information Science and Technology, University of Science and Technology of China, Hefei, China

2. Life Science School, University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

University of Science and Technology of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10210140/10138572.pdf?arnumber=10138572

Reference67 articles.

1. MTrack: Automated detection, tracking, and analysis of dynamic microtubules;kapoor;Sci Rep,2018

2. PyTorch: An imperative style, high-performance deep learning library;paszke;Proc Annu Conf Neural Inf Process Syst,0

3. Microtubule Tip Tracking and Tip Structures at the Nanometer Scale Using Digital Fluorescence Microscopy

4. Onnx: Open neural network exchange;bai,2019

5. Mask R-CNN

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