Prostate Cancer Cell Prediction from Histopathological Images using Convolutional Neural Network

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dc.contributor.advisorDr. Mohammad Monirujjaman Khan
dc.contributor.authorWatan Al Arafat
dc.contributor.authorMd. Mushfiqur Rahman
dc.contributor.id1731311042
dc.contributor.id1620003042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2026-04-22
dc.date.accessioned2026-04-22T09:23:06Z
dc.date.available2026-04-22T09:23:06Z
dc.date.issued2022
dc.description.abstractIn cancer research, pinpointing a patient's future response to treatment is crucial for making informed decisions. This study delves into a potential method for predicting the return of prostate cancer after surgery, utilizing imagery from tissue samples. Scientists analyzed a group of patients, categorizing them based on whether their cancer returned after treatment. To account for existing variations besides the cancer itself, they meticulously matched patients within the group based on factors like age, ethnicity, and disease severity. The proposed technique hinges on a sophisticated form of artificial intelligence known as deep learning. Uniquely, it employs two distinct AI models: one to pinpoint individual cells within the tissue, even in dense areas, and another to classify these cells. By analyzing these classified cells, the researchers were able to estimate, with promising accuracy, the likelihood of cancer recurrence in a patient. This method, if further validated, holds the potential to revolutionize treatment decisions for prostate cancer, offering a more personalized approach. The broader implications of this research extend beyond prostate cancer. This approach, with further development, might be adaptable to predicting treatment outcomes in various cancers. We have found the accuracy 93.33 percent. Keywords- Prostate; Cancer; Convolutional Neural Network; CNN; Deep Learning, prediction
dc.description.degreeUndergraduate
dc.identifier.cd600000908
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1649
dc.language.isoen
dc.publisherNorth South University
dc.rights©NSU Library
dc.titleProstate Cancer Cell Prediction from Histopathological Images using Convolutional Neural Network
oaire.citation.endPage39
oaire.citation.startPage1
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