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Leukocytes

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Detection of live breast cancer cells in bright-field microscopy images containing white blood cells by image analysis and deep learning.

Journal of biomedical optics
SIGNIFICANCE: Circulating tumor cells (CTCs) are important biomarkers for cancer management. Isolated CTCs from blood are stained to detect and enumerate CTCs. However, the staining process is laborious and moreover makes CTCs unsuitable for drug tes...

The Effect of Data Augmentation in Deep Learning Approach for Peripheral Blood Leukocyte Recognition.

Studies in health technology and informatics
Data augmentation is reported as a useful technique to generate a large amount of image datasets from a small image dataset. The aim of this study is to clarify the effect of data augmentation for leukocyte recognition with deep learning. We performe...

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

Optics express
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morpholog...

Classification of white blood cells using weighted optimized deformable convolutional neural networks.

Artificial cells, nanomedicine, and biotechnology
BACKGROUND: Machine learning (ML) algorithms have been widely used in the classification of white blood cells (WBCs). However, the performance of ML algorithms still needs to be addressed for being short of gold standard data sets, and even the imple...

Thousands of induced germline mutations affecting immune cells identified by automated meiotic mapping coupled with machine learning.

Proceedings of the National Academy of Sciences of the United States of America
Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasiona...

Leukocyte super-resolution via geometry prior and structural consistency.

Journal of biomedical optics
SIGNIFICANCE: Researchers have made great progress in single-image super-resolution (SISR) using deep convolutional neural networks. However, in the field of leukocyte imaging, the performance of existing SISR methods is still limited as it fails to ...

[Detection of white blood cells in microscopic leucorrhea images based on deep active learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The number of white blood cells in the leucorrhea microscopic image can indicate the severity of vaginal inflammation. At present, the detection of white blood cells in leucorrhea mainly relies on manual microscopy by medical experts, which is time-c...

Leukocyte recognition in human fecal samples using texture features.

Journal of the Optical Society of America. A, Optics, image science, and vision
Unlike urine or blood samples with a single background, human fecal samples contain large amounts of food debris, amorphous particles, and undigested plant cells. It is difficult to segment such impurities when mixed with leukocytes. Cell degradation...

Automated cell type discovery and classification through knowledge transfer.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and h...