Efficient Semantic Segmentation of Nuclei in Histopathology Images Using Segformer

Khaled, Marwan; Hammouda, Mostafa A.; Ali, Hesham; Elattar, Mustafa; Selim, Sahar

doi:10.1007/978-3-031-48593-0_6

Lecture Notes in Computer Science

2023

DOI: 10.1007/978-3-031-48593-0_6

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Efficient Semantic Segmentation of Nuclei in Histopathology Images Using Segformer

Marwan Khaled,

Mostafa A. Hammouda,

Hesham Ali

et al.

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2024

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Cited by 1 publication

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Virtual histopathology methods in medical imaging - a systematic review

Imran,

Shafi,

Ahmad

et al. 2024

BMC Med Imaging

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Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, often resulting in time-consuming processes and variability in diagnoses. Virtual histopathology offers a more consistent, and automated approach, employing techniques like machine learning, deep learning, and image processing to simulate staining and enhance tissue analysis. This review explores the strengths, limitations, and clinical applications of these methods, highlighting recent advancements in virtual histopathological approaches. In addition, important areas are identified for future research to improve diagnostic accuracy and efficiency in clinical settings.

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Virtual histopathology methods in medical imaging - a systematic review

Imran,

Shafi,

Ahmad

et al. 2024

BMC Med Imaging

View full text Add to dashboard Cite

show abstract

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Efficient Semantic Segmentation of Nuclei in Histopathology Images Using Segformer

Cited by 1 publication

References 16 publications

Virtual histopathology methods in medical imaging - a systematic review

Virtual histopathology methods in medical imaging - a systematic review

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