Advancing Malaria Identification From Microscopic Blood Smears Using Hybrid Deep Learning Frameworks
Abstract: Malaria is a mosquito-borne, life-threatening, and contagious disease that has caused thousands of fatalities in recent years. Due to inadequate detection, the inexperience of laboratory ...
ABSTRACT: This paper discusses the task of enhancing malaria detection in thick blood smear images by proposing a UNet-based denoising algorithm. Noise and artifacts in these images can compromise the ...
Abstract: Peripheral blood cell detection is essential for diagnosing and monitoring hematologic disorders. However, existing methods typically focus on a limited number of cell types (usually 3 to 10 ...
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