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Meet Bhatt edited this page Aug 11, 2025 · 8 revisions

Project Phoenix

The Phoenix is a creature of legend—consumed by flame, only to rise again from its own ashes, reborn and radiant. This project carries that same spirit into the realm of cervical cancer diagnostics. In every microscopic image lies a quiet battle between life and disease, and like the Phoenix, we believe in catching the fall before it happens. By teaching machines to recognize the earliest cellular shifts—those subtle signs of transformation—we aim to turn what could become devastation into a story of renewal. Not with myth, but with math. Not with magic, but with models. Because every early diagnosis is a chance to rise again—stronger, sooner, and with fire on your side.

Resources

Title Description Link
Github Repository Link to the Github repo with the primary code base Github Repository
Github Wiki Link to the Github Wiki to store the primary project documentation Github Wiki
Github Project Link to the Github Project for Project Management (Will need access) Github Project
Drive Link Link to the primary Google Drive to store all project related documents 6_Project Phoenix_Cervical Cancer Cell Classification
Literature Review Link to the Google Sheets with the details for Literature Review Project Phoenix_Literature Review
SipakMed Dataset Link to the SipakMed cervical cancer dataset SipakMed Cervical Cancer Dataset
Herlev Dataset Link to the Herlev cervical cancer dataset Herlev Dataset
The Cancer Imaging Archive Link to The Cancer Imaging Archive dataset TCGA-CESC - The Cancer Imaging Archive (TCIA)
Notebook LM Link to the Project Phoenix Notebook for research Project Phoenix Notebook LM
Cx22 Cervical Cell Nucleus Dataset Link to the Cx22 dataset with cervical cell nuclei labelling LGQ330/Cx22
Cervix93 Cytology Dataset and the Baseline Method Link to the Cervix93 Cytology dataset with manually annotated cervical nuclei and grade labels Cervix93 Cytology Dataset and the Baseline Method
Pretrained Backbone Comparison Link to the comparative study to determine which pretrained backbone would be the best fit for finetuning. Pretrained Backbone Comparitive Study

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