twpkevin06222/MasterThesis
Classification of Clinically Significant Prostate Cancer with 3D Multiparametric MRI with Deep Metric Learning.
This project helps radiologists and oncologists better classify clinically significant prostate cancer using 3D Multiparametric MRI scans. It takes the MRI image sequences (T2, DWI, ADC) as input and provides a classification result indicating the likelihood of significant cancer, along with the ability to retrieve visually similar cases. The goal is to reduce false positives in biopsies by offering more discriminative diagnostic support.
No commits in the last 6 months.
Use this if you need an advanced tool to aid in the precise classification of prostate cancer from MRI images, especially to reduce unnecessary biopsies.
Not ideal if you have a small dataset or require a tool that performs well without extensive hyperparameter tuning for margin-based loss functions.
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Mar 07, 2022
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