Handcrafted and Deep features based Classification of Scoliosis | [IEEE International Conference on Digital Futures and Transformative Technologies (ICoDT2) May 24-26, 2022 (Book of Abstracts) • 2022]

Author(s):

1. Joddat Fatima: Bahria University Islamabad,Pakistan

2. Mashood M. Mohsan: National University of Sciences & Technology Islamabad,Pakistan

3. Muhammad Umair Qaisar: National University of Sciences & Technology Islamabad,Pakistan

4. Muhammad Hamza: National University of Sciences & Technology Islamabad,Pakistan

5. Muhammad Zeshan Tahir: National University of Sciences & Technology Islamabad,Pakistan

6. Ghazzal Zaman: National University of Sciences & Technology Islamabad,Pakistan

Abstract:

The Spinal cord acts as the central transmission line connecting the Brain with all other body organs. Vertebrae are 33 uneven bones stacked over one another that holds the whole skeleton structure. Scoliosis is the threedimensional spinal deformity which commonly occurs during the growing age and erupts before puberty. It is further classified in two Shapes C and S. Our research work has two stages, in first stage we segment out the vertebral column using Mask-RCNN. The segmented column is used for features extraction and in stage two feature based classification is done for normal, C and S shape of scoliosis using AASCE2019 dataset. A comparative study on multiple image classification networks is also conducted and based on results EfficientNet-B4 is selected for formulation of hybrid feature set. The accuracy achieved using Random forest classifier, for handcrafted and deep features was up to 94.32% and 89.66%. Hybrid feature set formulated with combination of deep and handcrafted features attained accuracy up to 94.45%.

Page(s): 1-1

DOI: DOI not available

Published: Journal: IEEE International Conference on Digital Futures and Transformative Technologies (ICoDT2) May 24-26, 2022 (Book of Abstracts), Volume: 1, Issue: 1, Year: 2022

Keywords:

Scoliosis , MaskRCNN , AASCE2019 dataset

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