Efficacy Analysis of Fractured Bone on Hyper Spectral Imagery - Dr. T. Arumuga Maria Devi; Mrs. Ajitha S Raj; Selva Kumari S; Dr. M. Sathish Kumar; P. Ithaya Rani (Utilitas Mathematica, 2025)
Objectives: Detection of Fractures: Assess the ability of hyper spectral imagery to accurately detect fractures in bone structures. This involves identifying spectral signatures associated with fractured bone and developing algorithms for automated detection. Classification of Fracture Types: Different types of fractures (e.g., hairline fractures, compound fractures) may exhibit distinct spectral characteristics. Objectives should include classifying fracture types based on hyper spectral data to aid in diagnosis and treatment planning. Method: Data Acquisition: Acquire hyper spectral imagery data containing spectral information across a wide range of wavelengths. This data can be obtained from specialized hyper spectral imaging systems capable of capturing spectral signatures of the target area. Preprocessing: Correct for atmospheric effects and sensor artifacts to enhance the quality of the hyper spectral data. Perform radiometric calibration to convert raw spectral data into quantitative reflectance or absorbance values. Remove noise and irrelevant spectral bands to focus on informative spectral features relevant to fractured bone. Region of Interest (ROI) Selection: Identify the region of interest containing the fractured bone within the hyper spectral image. Define the boundaries of the fractured area and ensure that the ROI encompasses relevant spectral information. Findings: Detection Accuracy: The analysis may reveal the ability of hyper spectral imagery to accurately detect fractures in bone structures. This includes the sensitivity and specificity of fracture detection compared to ground truth data or conventional imaging methods. Classification of Fracture Types: Hyper spectral imaging may enable the differentiation of different types of fractures based on their spectral signatures. Findings may include the ability to distinguish between hairline fractures, compound fractures, and other fracture types. Quantification of Fracture Severity: The study may demonstrate the efficacy of hyper spectral imaging in quantifying fracture severity parameters such as size, displacement, and fragmentation. This could provide valuable information for clinical decision-making and treatment planning. Novelty: Non-Invasive Imaging: Hyper spectral imaging offers a non-invasive means of assessing fractures, unlike traditional methods such as X-rays or CT scans, which involve ionizing radiation. This reduces patient exposure to harmful radiation and provides a safer alternative for imaging fractures, especially in pediatric or pregnant populations. Comprehensive Spectral Information: Hyper spectral imagery captures spectral information across a wide range of wavelengths, providing a rich dataset for analysis. Unlike conventional imaging modalities that rely on anatomical structures, hyper spectral imaging exploits biochemical and molecular signatures, offering insights into tissue composition and pathology.