The advent of whole-slide imaging,faster image data generation,and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes...The advent of whole-slide imaging,faster image data generation,and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes in conjunction with clinical samples.In parallel,with continuous breakthroughs in object detection,image feature extraction,image classification and image segmentation,artificial intelligence(AI)is becoming the most beneficial technology for high-throughput analysis of image data in various biomedical imaging disciplines.Integrating digital images into biological workflows,advanced algorithms,and computer vision techniques expands the biologist’s horizons beyond the microscope slide.Here,we introduce recent developments in AI applied to microscopy in hematopathology.We give an overview of its concepts and present its applications in normal or abnormal hematopoietic cells identification.We discuss how AI shows great potential to push the limits of microscopy and enhance the resolution,signal and information content of acquired data.Its shortcomings are discussed,as well as future directions for the field.展开更多
基金This work was supported by grants from the National Key Research and Development Project of China[2021YFC2500300,2019YFA0801800]National Natural Science Foundation of China[82070109,62002153]+1 种基金Guangdong Basic and Applied Basic Research Foundation[2022A1515011253,2021A1515110653,2019A1515010784]China Postdoctoral Science Foundation[2020M682785].
文摘The advent of whole-slide imaging,faster image data generation,and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes in conjunction with clinical samples.In parallel,with continuous breakthroughs in object detection,image feature extraction,image classification and image segmentation,artificial intelligence(AI)is becoming the most beneficial technology for high-throughput analysis of image data in various biomedical imaging disciplines.Integrating digital images into biological workflows,advanced algorithms,and computer vision techniques expands the biologist’s horizons beyond the microscope slide.Here,we introduce recent developments in AI applied to microscopy in hematopathology.We give an overview of its concepts and present its applications in normal or abnormal hematopoietic cells identification.We discuss how AI shows great potential to push the limits of microscopy and enhance the resolution,signal and information content of acquired data.Its shortcomings are discussed,as well as future directions for the field.
