Council of Scientific and Industrial Research

National Informatics Centre Department of Electronics and Information Technology

Abhishek Gupta

Harish Kumar Sardana

Viren Sardana

Om Prakash Kharbanda

Bala Chakravarthy Neelapu

Srikanth Vasamsetti

Described herein is a method detecting a plurality of upper respiratory tract sub-regions automatically. Volume of interest (VOI) is identified based on the extraction of certain features, such as regional properties and shape-based features. The complete airway volume from a patient's data is identified by observing the area and eccentricity profiles of the certain volume/organ in the skull. Maxillary sinus area and eccentricity profile in the sagittal view is chosen in the present subject matter for level 1 VOI identification. Once a level 1VOI is identified, the other sub-regions existing in the same VOI are further identified as individual level 2 VOI. Level 3 VOI is extracted based on the shape and geometric features of the organ. The extracted level 3 VOI is considered as the active contour that is followed by the initialized contour for the accurate segmentation of upper airway sub-regions.

Method and system for automatic volumetric-segmentation of human upper respiratory tract

Embodiments of a method for detection of plurality of three-dimensional cephalometric landmarks in volumetric data are disclosed. In some embodiments, a three-dimensional matrix is developed by stacking of volumetric data and the bony structure is segmented through thresholding. Initially a seed point is searched for initializing the process of landmark detection. Two three-dimensional distance vectors are used to define and obtain the Volume of Interest (VOI). First 3-D distance vector helps to identify Empirical Point and consecutively second gives dimensions of the VOI. Three-dimensional contours of anatomical structure are traced in the estimated VOI. Cephalometric landmarks are identified on the boundaries of traced anatomical geometry, based on corresponding Mathematical Entities. Detected landmark can be used as a Reference Point for further detection of landmarks. Estimating the VOI and detection of points continues till all desired landmarks are detected. The detection procedure gives three-dimensional coordinate locations of the landmarks.

Method for automatic detection of anatomical landmarks in volumetric data

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Chandigarh, India

Abhishek Gupta