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Microscopy

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Computer Aided Solution for Automatic Segmenting and Measurements of Blood Leucocytes Using Static Microscope Images.

Journal of medical systems
Blood leucocytes segmentation in medical images is viewed as difficult process due to the variability of blood cells concerning their shape and size and the difficulty towards determining location of Blood Leucocytes. Physical analysis of blood tests...

SetSVM: An Approach to Set Classification in Nuclei-Based Cancer Detection.

IEEE journal of biomedical and health informatics
Due to the importance of nuclear structure in cancer diagnosis, several predictive models have been described for diagnosing a wide variety of cancers based on nuclear morphology. In many computer-aided diagnosis (CAD) systems, cancer detection tasks...

Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception.

Journal of healthcare engineering
This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucleated cell usually stained that is salient obviously, the proposed method is suitable to segment nuc...

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Biosensors & bioelectronics
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...

Egg Excretion does not Increase after Exercise: Implications for Diagnostic Testing.

The American journal of tropical medicine and hygiene
Children are frequently invited to exercise before micturition, as it is believed that this activity will result in higher egg excretion, and hence, increases sensitivity of microscopic diagnoses. However, the evidence of this recommendation is scan...

Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments.

Scientific reports
For single-cell experiments, it is important to accurately count the number of viable cells in a nanoliter well. We used a deep learning-based convolutional neural network (CNN) on a large amount of digital data obtained as microscopic images. The tr...

Deep Learning in Microscopy Image Analysis: A Survey.

IEEE transactions on neural networks and learning systems
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...

A deep convolutional neural network for classification of red blood cells in sickle cell anemia.

PLoS computational biology
Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological...

A dictionary learning approach for human sperm heads classification.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classifi...