Segmify: A Deep Learning-Based Interactive Tool for Real-Time Cell Segmentation and Morphological Analysis

Accurately segmenting cells in microscopy images is vital for biomedical research, yet remains challenging due to issues like overlapping cells, noise, and low contrast. We address these challenges with an interactive dashboard powered by a U-Net++ model. Our system integrates Contrast Limited Adaptive Histogram Equalization (CLAHE) for enhanced segmentation in low-contrast images, along with custom loss functions and data augmentation to boost accuracy. The tool supports both automated and manual segmentation, allowing real-time parameter adjustments and morphological analysis on the cellular level. This versatile platform provides researchers with the flexibility to adapt to diverse datasets, ensuring high-quality results.