Automated methods for sella turcica segmentation on cephalometric radiographic data using deep learning (CNN) techniques.

Journal: Oral radiology
PMID:

Abstract

OBJECTIVE: The objective of this work is to present a novel technique using convolutional neural network (CNN) architectures for automatic segmentation of sella turcica (ST) on cephalometric radiographic image dataset. The proposed work suggests possible deep learning approaches to distinguish ST on complex cephalometric radiographs using deep learning techniques.

Authors

  • Kaushlesh Singh Shakya
    Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
  • Amit Laddi
    CSIR-Central Scientific Instruments Organisation, Chandigarh, 160030, India.
  • Manojkumar Jaiswal
    Oral Health Sciences Centre, PGIMER, Chandigarh, 160012, India. drmanojjaiswal@yahoo.in.