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- W4387570264 abstract "Abstract Early cancer detection is critical in enhancing a patient’s clinical results. Cervical cancer detection from a large number of whole slide images generated regularly in a clinical setting is a complex and time-consuming task. As a result, we require an efficient and accurate model for early cancer diagnosis, especially cervical cancer as it can be fully prevented if detected in an early stage. This study focuses on in-depth writing on current methodologies for cervical cancer segmentation and characterization from the whole cervical slide. It combines the state of their specialty’s performance measurement with the quantitative evaluation of cutting-edge techniques. Numerous publications over the last eleven years (2011-2022) clearly outline various cervical imaging methods over multiple blocks. And this review shows different types of algorithms used in each processing stage of detection. The study clearly indicates the advancements in the automation field and the necessity of the same." @default.
- W4387570264 created "2023-10-13" @default.
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- W4387570264 date "2023-10-01" @default.
- W4387570264 modified "2023-10-13" @default.
- W4387570264 title "Investigation of Cervical Cancer Detection from Whole Slide Imaging" @default.
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- W4387570264 doi "https://doi.org/10.1088/1742-6596/2571/1/012002" @default.
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