FRONTIERS IN BIOIMAGE INFORMATICS METHODOLOGY

This unique compendium provides state-of-the-art computational methodology and applications in bioimage informatics. It covers cutting-edge technology developments in biological image analysis, where images come from new modalities and are often large scale, high throughput and high dimensional. The book reflects advances in intelligent algorithms for tasks such as biological image segmentation, reconstruction, and object tracking.

Contributed by world renowned researchers, this useful reference text presents case studies that can potentially help readers find approaches and resources to address their imminent scientific problems.

Contents:

• Preface
• About the Editors
• Applications:
  • The Advance of Computational Methods in Cryo-Electron Tomography (Renmin Han and Min Xu)
  • Computational Workflows for Following Processes during Key Events in the Yeast Life Cycle (David Hörl)
  • Neuronal Image Reconstruction (Yufeng Liu, Kaifeng Chen, and Hanchuan Peng)
  • Synapse Detection and Quantification in Fluorescent Images: A Survey (Yizhi Wang, Xuelong Mi, Boyu Lyu, Mengfan Wang, and Guoqiang Yu)
  • AI-Based Computational Pathology and Its Contribution to Precision Medicine (Haoda Lu, Longjie Li, Kokhaur Ong, Yufan Wang, Yiping Jiao, Xiangxue Wang, Chengfei Cai, Jing Zhang, Jun Hou, Huanfen Zhao, Hualei Gan, Wanyuan Chen, Xinmi Huo, Lihua Zhang, Weimiao Yu, and Jun Xu)
  • Automated Quantification of Animal Behavior in Video Recordings (Yujia Hu)
• Methods:
  • Data-Efficient Instance Segmentation for Multi-modal Microscopy Images (Dongnan Liu and Weidong Cai)
  • Transfer Learning from Synthetic Data for Cell Segmentation and Tracking (Andreas Milias-Argeitis and Herbert Kruitboschh)
  • Deep Learning-Based 3D Neuron Segmentation Using Synthesized Data (Qiufu Li, Linlin Shen, and Qiong Liu)
  • Image Stitching of Teravoxel-Sized Whole-Brain Microscopy Data (Liya Ding, Yabo Li, Jiayi Ding, Xiaoli Qi, Hu Zhao, and Hanchuan Peng)
• Index

Readership: Researchers, professionals, academics and graduate students in image analysis, AI, bioinformatics, and neural networks.