AIMC Topic: Leukocytes

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Augmentation of Infrared Microscopy of White Blood Cells and Medical Measures for Rapid and Accurate Diagnosis of Bacterial or Viral Infections in Febrile Pediatric Oncology Patients: An Expert System-Based Study.

Analytical chemistry
Infectious diseases, a major contributor to high mortality rates, often exhibit similar symptoms, despite variations in immune responses to bacterial or viral infections. Rapidly differentiating bacterial infections from viral infections in febrile p...

Deep learning based semantic segmentation of leukemia effected white blood cell.

PloS one
Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red blood cells. This paper represents the segmentation of WBCs from blood smear images. It is a complex and...

Improving Interpretability of Leucocyte Classification with Multimodal Network.

Studies in health technology and informatics
White blood cell classification plays a key role in the diagnosis of hematologic diseases. Models can perform classification either from images or based on morphological features. Image-based classification generally yields higher performance, but fe...

Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN.

Mathematical biosciences and engineering : MBE
An automatic recognizing system of white blood cells can assist hematologists in the diagnosis of many diseases, where accuracy and efficiency are paramount for computer-based systems. In this paper, we presented a new image processing system to reco...

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 ...