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Malaria, a life-threatening disease, infects millions of people every year throughout the world demanding faster diagnosis for proper treatment before any damages occur. In this paper, an end-to-end deep learning-based approach is proposed…

计算机视觉与模式识别 · 计算机科学 2020-12-11 Tanvir Mahmud , Shaikh Anowarul Fattah

Malaria is a parasitic infection that poses a significant burden on global health. It kills one child every 30 seconds and over one million people annually. If diagnosed in a timely manner, however, most people can be effectively treated…

计算机视觉与模式识别 · 计算机科学 2021-08-10 Vignav Ramesh

Malaria remains one of the most pressing public health concerns globally, causing significant morbidity and mortality, especially in sub-Saharan Africa. Rapid and accurate diagnosis is crucial for effective treatment and disease management.…

图像与视频处理 · 电气工程与系统科学 2024-07-01 Saurabh Sawant , Anurag Singh

Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species and (ii) quantitate high-parasitemia infections. Full automation of malaria…

Malaria is a life-threatening mosquito-borne blood disease, hence early detection is very crucial for health. The conventional method for the detection is a microscopic examination of Giemsa-stained blood smears, which needs a highly…

计算机视觉与模式识别 · 计算机科学 2020-06-24 Neeru Singla , Vishal Srivastava

Point of care diagnostics using microscopy and computer vision methods have been applied to a number of practical problems, and are particularly relevant to low-income, high disease burden areas. However, this is subject to the limitations…

计算机视觉与模式识别 · 计算机科学 2016-08-11 John A. Quinn , Rose Nakasi , Pius K. B. Mugagga , Patrick Byanyima , William Lubega , Alfred Andama

Deep learning based models have had great success in object detection, but the state of the art models have not yet been widely applied to biological image data. We apply for the first time an object detection model previously used on…

Malaria, a fatal but curable disease claims hundreds of thousands of lives every year. Early and correct diagnosis is vital to avoid health complexities, however, it depends upon the availability of costly microscopes and trained experts to…

计算机视觉与模式识别 · 计算机科学 2022-04-19 Waqas Sultani , Wajahat Nawaz , Syed Javed , Muhammad Sohail Danish , Asma Saadia , Mohsen Ali

Malaria remains a major global health challenge, particularly in low-resource settings where access to expert microscopy may be limited. Deep learning-based computer-aided diagnosis (CAD) systems have been developed and demonstrate…

Malaria remains a prevalent health concern in regions with tropical and subtropical climates. The cause of malaria is the Plasmodium parasite, which is transmitted through the bites of infected female Anopheles mosquitoes. Traditional…

计算机视觉与模式识别 · 计算机科学 2025-12-30 Md. Ismiel Hossen Abir , Awolad Hossain

Malaria is a female anopheles mosquito-bite inflicted life-threatening disease which is considered endemic in many parts of the world. This article focuses on improving malaria detection from patches segmented from microscopic images of red…

图像与视频处理 · 电气工程与系统科学 2019-07-25 Aimon Rahman , Hasib Zunair , M Sohel Rahman , Jesia Quader Yuki , Sabyasachi Biswas , Md Ashraful Alam , Nabila Binte Alam , M. R. C. Mahdy

Deep learning has emerged as the predominant solution for classifying medical images. We intend to apply these developments to the ultra-widefield (UWF) retinal imaging dataset. Since UWF images can accurately diagnose various retina…

图像与视频处理 · 电气工程与系统科学 2025-03-25 Siwon Kim , Wooyung Yun , Jeongbin Oh , Soomok Lee

Malaria remains a significant global health challenge, necessitating rapid and accurate diagnostic methods. While computer-aided diagnosis (CAD) tools utilizing deep learning have shown promise, their generalization to diverse clinical…

Malaria parasites pose a significant global health burden, causing widespread suffering and mortality. Detecting malaria infection accurately is crucial for effective treatment and control. However, existing automated detection techniques…

计算机视觉与模式识别 · 计算机科学 2024-12-18 Abraham G Taye , Sador Yemane , Eshetu Negash , Yared Minwuyelet , Moges Abebe , Melkamu Hunegnaw Asmare

Malaria is a potentially fatal plasmodium parasite injected by female anopheles mosquitoes that infect red blood cells and millions worldwide yearly. However, specialists' manual screening in clinical practice is laborious and prone to…

图像与视频处理 · 电气工程与系统科学 2024-03-21 Saddam Hussain Khan , Tahani Jaser Alahmadi

Malaria is usually diagnosed by a microbiologist by examining a small sample of blood smear. Reducing mortality from malaria infection is possible if it is diagnosed early and followed with appropriate treatment. While the WHO has set…

计算机视觉与模式识别 · 计算机科学 2023-03-22 Onyekachukwu R. Okonji

Optical imaging systems are generally limited by the depth of field because of the nature of the optics. Therefore, extending depth of field (EDoF) is a fundamental task for meeting the requirements of emerging visual applications. To solve…

计算机视觉与模式识别 · 计算机科学 2024-10-01 Zhilong Li , Kejun Wu , Qiong Liu , You Yang

Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information. Extended depth of field (EDoF) imaging is a challenging ill-posed problem and has been extensively addressed in…

图像与视频处理 · 电气工程与系统科学 2020-05-27 Ugur Akpinar , Erdem Sahin , Monjurul Meem , Rajesh Menon , Atanas Gotchev

Malaria, a mosquito-borne disease caused by a parasite, kills over 1 million people globally each year. People, if left untreated, may develop severe complications, leading to death. Effective and accurate diagnosis is important for the…

图像与视频处理 · 电气工程与系统科学 2020-09-02 Alexander Tao , Boran Han

The recent development of deep learning large models in medicine shows remarkable performance in medical image analysis and diagnosis, but their large number of parameters causes memory and inference latency challenges. Knowledge…

计算机视觉与模式识别 · 计算机科学 2024-09-19 Shaojie Li , Zhaoshuo Diao
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