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Prototype System for Supporting Urologists in Bladder Tumor Detection

Principal Investigator
Name
Jaime Hugo Puebla Lomas
Degrees
Ph.D.
Institution
Instituto Politécnico Nacional
Position Title
Faculty member
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCOI-1527
Initial CDAS Request Approval
Apr 18, 2024
Title
Prototype System for Supporting Urologists in Bladder Tumor Detection
Summary
The bladder is one of the most important organs in the body, as its function is vital for humans. When abnormalities occur in it, it is advisable to perform relevant studies or "scans". Physicians obtain images to analyze the problem being presented; however, a diagnosis of this complexity requires more than a single review to determine a result regarding the patient's health. For this reason, the effective use of image analysis techniques and classification Machine Learning algorithms is considered to address this issue. This final project aims to develop a prototype system to assist Urologists in the pre-diagnosis process, determining through medical imaging whether a tumor exists and at what stage, as well as visualizing the anomaly found.
Aims

1. Establish a knowledge base through a set of magnetic resonance images validated by a recognized medical
institution (Database).
2. Determine the most discriminant characteristics for the training image set.
3. Train a Classifier model to assist Urologists in pre-diagnosing bladder tumors.
4. Train the knowledge base using pattern recognition techniques.
5. Develop a testing module to visualize anomalies in medical images and classify the disease.

Collaborators

Almeraya Pineda Kimberly Jovana - Student of the Artificial Intelligence Engineering program at ESCOM, Enrollment Number: 2019630153, Phone: +52 55 6790 5835, Email: kimber.jap@gmail.com

Ruiz Uvalle Sebastian - Student of the Artificial Intelligence Engineering program at ESCOM, Enrollment Number: 2020630433, Phone: +52 55 4117 8683, Email: se.ru.uv.12@gmail.com

Vargas Soriano Flor Arlette - Student of the Artificial Intelligence Engineering program at ESCOM, Enrollment Number: 2021630710, Phone: +52 56 1453 6541, Email: florarletvas97@gmail.com