[HTML][HTML] A bird's-eye view of deep learning in bioimage analysis
E Meijering - Computational and structural biotechnology journal, 2020 - Elsevier
Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …
solving data analysis problems in virtually all fields of science and engineering. Also in …
Pooled genetic screens with image‐based profiling
Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and
organismal scales, is encoded through a combination of genetic and epigenetic factors in …
organismal scales, is encoded through a combination of genetic and epigenetic factors in …
Leukocytes image classification using optimized convolutional neural networks
Hematologic diseases and blood disorders can be studied through the microscopic or
chemical examination of blood smear images. Many researchers work on identifying …
chemical examination of blood smear images. Many researchers work on identifying …
[图书][B] Genetic programming for image classification: An automated approach to feature learning
This book offers several new GP approaches to feature learning for image classification.
Image classification is an important task in computer vision and machine learning with a …
Image classification is an important task in computer vision and machine learning with a …
[HTML][HTML] Combining imaging flow cytometry and machine learning for high-throughput schistocyte quantification: a SVM classifier development and external validation …
J Demagny, C Roussel, M Le Guyader, E Guiheneuf… - …, 2022 - thelancet.com
Background Schistocyte counts are a cornerstone of the diagnosis of thrombotic
microangiopathy syndrome (TMA). Their manual quantification is complex and alternative …
microangiopathy syndrome (TMA). Their manual quantification is complex and alternative …
Deep learning‐enabled imaging flow cytometry for high‐speed Cryptosporidium and Giardia detection
Imaging flow cytometry has become a popular technology for bioparticle image analysis
because of its capability of capturing thousands of images per second. Nevertheless, the …
because of its capability of capturing thousands of images per second. Nevertheless, the …
Cell phenotype classification based on joint of texture information and multilayer feature extraction in DenseNet
Cell phenotype classification is a critical task in many medical applications, such as protein
localization, gene effect identification, and cancer diagnosis in some types. Fluorescence …
localization, gene effect identification, and cancer diagnosis in some types. Fluorescence …
Cell recognition based on atomic force microscopy and modified residual neural network
J Wang, M Gao, L Yang, Y Huang, J Wang… - Journal of Structural …, 2023 - Elsevier
Cell recognition methods are in high demand in cell biology and medicine, and the method
based on atomic force microscopy (AFM) shows a great value in application. The difference …
based on atomic force microscopy (AFM) shows a great value in application. The difference …
A computer vision-based approach for tick identification using deep learning models
Simple Summary Ticks are ectoparasites of humans, livestock, and wild animals and, as
such, they are a nuisance, as well as vectors for disease transmission. Since the risk of tick …
such, they are a nuisance, as well as vectors for disease transmission. Since the risk of tick …
Machine learning and feature analysis of the cortical microtubule organization of Arabidopsis cotyledon pavement cells
D Yoshida, K Akita, T Higaki - Protoplasma, 2023 - Springer
The measurement of cytoskeletal features can provide valuable insights into cell biology. In
recent years, digital image analysis of cytoskeletal features has become an important …
recent years, digital image analysis of cytoskeletal features has become an important …