Hair Cluster Detection Model Based on Dermoscopic Images
February 2024
in “
Frontiers in physics
”
TLDR The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
The document presents a new model for detecting sparse hair clusters using dermoscopic images, which incorporates an improved object detection neural network. The model features a Multi-Level Feature Fusion Module for extracting and combining features at various levels, and a Channel-Space Dual Attention Module that enhances detection precision by considering both channel and spatial dimensions. The model outperformed existing methods in accuracy and efficiency when tested on self-annotated data, suggesting its potential as a valuable tool for early detection and treatment of hair loss, as well as aiding medical professionals in diagnosis and treatment planning.
