A deep learning approach for segmentation of red blood cell images and malaria detection

Keyphrases

• Malaria 100%
• Red Blood Cells 100%
• Blood Cell Images 100%
• Deep Learning Methods 100%
• Malaria Diagnosis 100%
• Image Detection 100%
• Mortality Rate 33%
• Illness 33%
• Protozoan Parasites 33%
• Plasmodium 33%
• Healthcare Professionals 33%
• Deep Learning 33%
• Erythrocytes 33%
• Malaria Cases 33%
• Antimalarial Activity 33%
• Pathologist 33%
• Convolutional Neural Network 33%
• Global Accuracy 33%
• Peripheral Blood Film 33%
• Design Validation 33%
• Three-stage pipeline 33%
• Design Training 33%
• Digital Pathology 33%
• Light Microscopy 33%
• Design Testing 33%
• Graphics Processing Unit 33%
• Segmentation Neural Networks 33%

Biochemistry, Genetics and Molecular Biology

• Mortality Rate 100%
• Protozoon 100%
• Plasmodium 100%
• Hemocyte 100%
• Blood Film 100%
• Digital Pathology 100%

Immunology and Microbiology

• Mortality Rate 100%
• Protozoa 100%
• Plasmodium 100%
• Hemocyte 100%
• Erythrocyte 100%
• Light Microscopy 100%