Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images

Sivaramakrishnan Rajaraman, Sameer Antani, Mahdieh Poostchi, +5

PeerJ

CNN-based image analysis for malaria diagnosis

Zhaohui Liang, Andrew J. Powell, Ilker Ersoy, +10

Convolutional Neural NetworkEngineeringMachine LearningMalariaDigital Pathology +18

Automated image processing method for the diagnosis and classification of malaria on thin blood smears

Nicholas E. Ross, Charles J. Pritchard, David M. Rubin, +1

Medical & Biological Engineering & Computing

Image Processing MethodImage AnalysisEngineeringMedicineMalaria +8

Machine learning approach for automated screening of malaria parasite using light microscopic images

Dev Kumar Das, Madhumala Ghosh, Mallika Pal, +2

Micron

Light Microscopic ImagesImage AnalysisMachine LearningEngineeringAutomated Screening +12

Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears

Feng Yang, Mahdieh Poostchi, Hang Yu, +6

IEEE Journal of Biomedical and Health Informatics

Evaluations of deep convolutional neural networks for automatic identification of malaria infected cells

Yuhang Dong, Zhuocheng Jiang, Hongda Shen, +5

Convolutional Neural NetworkMedical Image SegmentationEngineeringMachine LearningMalaria +17

Malaria Parasite Detection From Peripheral Blood Smear Images Using Deep Belief Networks

Dhanya Bibin, Madhu S. Nair, P. Punitha

IEEE Access

Convolutional Neural NetworkEngineeringMachine LearningMalariaDiagnosis +23

Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images

Sivaramakrishnan Rajaraman, Stefan Jaeger, Sameer Antani

PeerJ

Convolutional neural network‐based malaria diagnosis from focus stack of blood smear images acquired using custom‐built slide scanner

G. Gopakumar, Swetha Murali, Sai Siva Gorthi, +1

Journal of Biophotonics

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis

Allisson Dantas de Oliveira, Clara Prats, Mateu Espasa, +7

JMIR Research Protocols