Deep learning based neuronal soma detection and counting for Alzheimer's disease analysis.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 10, 2021

Abstract

BACKGROUND AND OBJECTIVE: Alzheimer's Disease (AD) is associated with neuronal damage and decrease. Micro-Optical Sectioning Tomography (MOST) provides an approach to acquire high-resolution images for neuron analysis in the whole-brain. Application of this technique to AD mouse brain enables us to investigate neuron changes during the progression of AD pathology. However, how to deal with the huge amount of data becomes the bottleneck.

Authors

  • Qiufu Li
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Hanbang Liang
    Computer Vision Institute, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, 518060, China; AI Research Center for Medical Image Analysis and Diagnosis, Shenzhen University, Shenzhen 518060, China; Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China.
  • Hui Gong
    Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.
  • Liang Jiang
    College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, 518055, China. Electronic address: fredjiang240@126.com.
  • Qiong Liu
    Medical College, Hubei University of Arts and Science, China; XiangYang Central Hospital, China.
  • Linlin Shen

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