Automated malarial retinopathy detection using transfer learning and multi-camera retinal images q

Cerebral malaria (CM) is a fatal syndrome found commonly in children less than 5 years old in Sub-saharan Africa and Asia. The retinal signs associated with CM are known as malar-ial retinopathy (MR), and they include highly specific retinal lesions such as whitening and hemorrhages. Detecting these lesions allows the detection of CM with high specificity. Up to 23% of CM, patients are over-diagnosed due to the presence of clinical symptoms also related to pneumonia, meningitis, or others. Therefore, patients go untreated for these pathologies, resulting in death or neurological disability. It is essential to have a low-cost and high-specificity diagnostic technique for CM detection, for which We developed a method based on transfer learning (TL). Models pre-trained with TL select the good quality retinal images, which are fed into another TL model to detect CM. This approach shows a 96% specificity with low-cost retinal cameras. (c) 2022 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Automated summary

Cerebral malaria (CM) is a fatal syndrome commonly observed in children under 5 in Sub-saharan Africa and Asia. The presence of retinal lesions known as malarial retinopathy (MR), including whitening and hemorrhages, is highly specific to CM. Over-diagnosis of CM occurs in up to 23% of cases due to similar clinical symptoms with pneumonia or meningitis, leading to untreated conditions and potential death or disability. A low-cost and high-specificity diagnostic technique based on transfer learning (TL) has been developed to detect CM, achieving a 96% specificity using inexpensive retinal cameras.