AIMC Topic: Erythrocytes

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Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences Nov 28, 2022
BACKGROUND AND PURPOSE: Thrombus red blood cell (RBC) content has been shown to be a significant factor influencing the efficacy of acute ischemic stroke treatment. In this study, our objective was to evaluate the ability of convolutional neural netw...
Middle Aged Neural Networks, Computer Deep Learning Erythrocytes Aged Female Humans Ischemic Stroke Intracranial Thrombosis Male Multiparametric Magnetic Resonance Imaging Stroke Thrombosis
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Perioperative Red Cell Line Trend following Robot-Assisted Radical Prostatectomy for Prostate Cancer.

Medicina (Kaunas, Lithuania) Oct 25, 2022
Background and Objective: Blood loss represents a long-standing concern of radical prostatectomy (RP). This study aimed to assess how red line cell values changed following robot-assisted radical prostatectomy (RARP) for prostate cancer (PCa). Materi...
Robotics Prostatic Neoplasms Robotic Surgical Procedures Treatment Outcome Cell Line Erythrocytes Prostatectomy Humans Male
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A novel deep learning approach for sickle cell anemia detection in human RBCs using an improved wrapper-based feature selection technique in microscopic blood smear images.

Biomedizinische Technik. Biomedical engineering Oct 6, 2022
Sickle Cell Anemia (SCA) is a disorder in Red Blood Cells (RBCs) of human blood. Children under five years and pregnant women are mostly affected by SCA. Early diagnosis of this ailment can save lives. In recent years, the computer aided diagnosis of...
Humans Databases, Factual Pregnancy Deep Learning Female Child, Preschool Anemia, Sickle Cell Diagnosis, Computer-Assisted Child Erythrocytes
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Automatic analysis system for abnormal red blood cells in peripheral blood smears.

Microscopy research and technique Aug 2, 2022
The type and ratio of abnormal red blood cells (RBCs) in blood can be identified through peripheral blood smear test. Accurate classification is important because the accompanying diseases indicated by abnormal RBCs vary. In clinical practice, this t...
Support Vector Machine Microscopy Erythrocytes Machine Learning Algorithms
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Detection of WBC, RBC, and Platelets in Blood Samples Using Deep Learning.

BioMed research international Jul 14, 2022
A blood count is one of the most important diagnostic tools in medicine and one of the most common procedures. It can reveal important changes in the body and is commonly used as the first stage in the process of evaluating patients' health. Even tho...
Erythrocytes Blood Platelets Deep Learning Leukocytes Laboratories Humans
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Explainable Transformer-Based Deep Learning Model for the Detection of Malaria Parasites from Blood Cell Images.

Sensors (Basel, Switzerland) Jun 8, 2022
Malaria is a life-threatening disease caused by female anopheles mosquito bites. Various plasmodium parasites spread in the victim's blood cells and keep their life in a critical situation. If not treated at the early stage, malaria can cause even de...
Plasmodium Parasites Female Animals Malaria Erythrocytes Deep Learning
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Simultaneous phenotyping of five Rh red blood cell antigens on a paper-based analytical device combined with deep learning for rapid and accurate interpretation.

Analytica chimica acta Apr 5, 2022
Both the ABO and Rhesus (Rh) blood groups play crucial roles in blood transfusion medicine. Herein, we report a simple and low-cost paper-based analytical device (PAD) for phenotyping red blood cell (RBC) antigens. Using this Rh typing format, 5 Rh a...
Deep Learning Antigens Rh-Hr Blood-Group System Blood Group Antigens Antibodies Erythrocytes
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Deep Learning-Based Phenotypic Assessment of Red Cell Storage Lesions for Safe Transfusions.

IEEE journal of biomedical and health informatics Mar 7, 2022
This study presents a novel approach to automatically perform instant phenotypic assessment of red blood cell (RBC) storage lesion in phase images obtained by digital holographic microscopy. The proposed model combines a generative adversarial networ...
Deep Learning Image Processing, Computer-Assisted Holography Erythrocytes Humans Neural Networks, Computer Aging
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Assessing red blood cell deformability from microscopy images using deep learning.

Lab on a chip Dec 21, 2021
Red blood cells (RBCs) must be highly deformable to transit through the microvasculature to deliver oxygen to tissues. The loss of RBC deformability resulting from pathology, natural aging, or storage in blood bags can impede the proper function of t...
Microscopy Erythrocytes Erythrocyte Count Humans Deep Learning Erythrocyte Deformability
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Imaging flow cytometry data analysis using convolutional neural network for quantitative investigation of phagocytosis.

Biotechnology and bioengineering Nov 18, 2021
Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor-mediated phagocytosis has relied upon immunotherapy that has become of particular interest for the treatment of cancer ...
Mice Animals Erythrocytes Phagocytosis Flow Cytometry Image Processing, Computer-Assisted Neural Networks, Computer Macrophages, Peritoneal Algorithms
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