Recognition and 3D Visualization of Human Body Parts and Bone Areas Using CT Images
نویسندگان
چکیده
Abstract The advent of medical imaging significantly assisted in disease diagnosis and treatment. This study introduces to a framework for detecting several human body parts Computerised Tomography (CT) images formatted DICOM files. In addition, the method can highlight bone areas inside CT transform 2D slices into visual 3D model illustrate structure parts. Firstly, we leveraged shallow convolutional Neural Networks classify detect each part. Then, Grad-CAM was applied areas. Finally, Insight Visualization libraries were utilized visualize slides As result, classifiers achieved 98 % F1-score classification on image dataset, including 1234 capturing from woman training phase 1245 male testing. distinguishing between non-bone reach 97 dataset generated by setting threshold value reveal images. Moreover, Grad-CAM-based approach provide clear, accurate visualizations with segmented bones image. Also, successfully converted slice part lively that provided more intuitive view any angle. proposed is expected an interesting tool supporting doctors image-based diagnosis.
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ژورنال
عنوان ژورنال: Applied Computer Systems
سال: 2023
ISSN: ['2255-8691', '2255-8683']
DOI: https://doi.org/10.2478/acss-2023-0007