Automated Scoliosis Detection Module

By Tabitha Janumala

Our "Automated Scoliosis Detection Module" is an advanced software solution aimed at transforming the detection and progression monitoring of scoliosis disease. Scoliosis, characterized by abnormal spinal curvature, requires early identification and regular monitoring to prevent further complications. Our module addresses this critical need by utilizing cutting-edge technology and machine learning algorithms.

Integrating seamlessly with existing medical imaging systems, such as X-ray and MRI, our module analyzes spinal images with exceptional precision. By employing sophisticated image processing techniques, it extracts crucial features and landmarks related to scoliosis.

These extracted features are then fed into a trained deep learning model, enabling accurate and automated scoliosis detection. The module assesses the severity of the curvature and tracks disease progression over time, providing valuable insights for medical professionals and patients alike.

By automating the detection and progression monitoring, our "Automated Scoliosis Detection Module" streamlines the workflow for healthcare providers, reducing time and effort in manual evaluations. This leads to earlier interventions and better patient outcomes.

With enhanced sensitivity and reliability, our module empowers medical practitioners to deliver timely and personalized care, optimizing the management of scoliosis for improved patient well-being and long-term quality of life.

• Format: Paperback
• Language: English
• ISBN: 8256484829
• ISBN13: 9788256484829
• Release Date: July 2023
• Publisher: Haji Publisher
• Length: 70 Pages
• Weight: 0.23 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"