Necrobiosis Lipoidica – A Skin Disease in Diabetic Patients
This project focuses on necrobiosis lipoidica, a chronic granulomatous skin disease most commonly associated with diabetes mellitus. The condition typically presents as well-demarcated plaques on the lower legs and is characterized histologically by collagen degeneration, granulomatous inflammation, and vascular changes. The project explores the clinical and histopathological features of necrobiosis lipoidica to improve understanding and recognition of the disease.
Mentor Details:
Prof. Iris Barshak
Mentor Details:
Requirments:
Identify key histopathological features associated with the disease.
Problem Statement
Necrobiosis lipoidica is a rare but clinically significant skin manifestation of diabetes that can be difficult to diagnose due to overlapping features with other granulomatous or inflammatory skin disorders. Delayed or incorrect diagnosis may lead to chronic ulceration and patient morbidity. Improved characterization and awareness of its histopathological features are needed to support accurate diagnosis and management.
Project Objectives
Identify key histopathological features associated with the disease.
Technical Scope
Image analysis
Object detection
Segmentation
Required Knowledge and Prerequisites
Core Requirements
Understanding of fundamental computer vision concepts
Experience with convolutional neural networks (CNNs)
Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow)
Recommended Background
Ability to work with image and video datasets
Project Difficulty and Expected Level
Overall Difficulty: Medium
This project is well-suited for:
Teams of 1–3 students
This project can also be done coding free with the DeePathology STUDIO
Expected Outcomes
Optimized Necrobiosis Lipoidica detection