A pilot study for segmentation of pharyngeal and sino-nasal airway subregions by automatic contour initialization

Neelapu, Bala Chakravarthy; Kharbanda, Om Prakash; Sardana, Viren; Gupta, Abhishek; Vasamsetti, Srikanth; Balachandran, Rajiv; Rana, Shailendra Singh; Sardana, Harish Kumar

doi:10.1007/s11548-017-1650-1

Cited by 22 publications

(14 citation statements)

References 30 publications

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“…A fully automatic segmentation, consisting of automatic contour initialisation and active contour segmentation, has also been proposed for sinonasal structures; 9 when compared with manual segmentation performed by two experienced operators, it showed precision and an F-score greater than 80%.…”

Section: Resultsmentioning

confidence: 99%

Segmentation procedures for the assessment of paranasal sinuses volumes

et al. 2020

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Background The paranasal sinuses are complex anatomical structures, characterised by highly variable shape, morphology and size. With the introduction of multidetector scanners and the development of many post-processing possibilities, computed tomography became the gold standard technique to image the paranasal sinuses. Segmentation allows the extraction of metrical and shape data of these anatomical components that can be applied for diagnostic, education, surgical planning and simulation, and to plan minimally invasive interventions in otorhinolaryngology and neurosurgery. Discussion Our aim was to provide a review of the existing literature on segmentation, its types and application, and the data obtained from this procedure. The literature search was conducted on PubMed (including Medline), ScienceDirect and Google Scholar databases, using the keywords as follows: ‘paranasal sinuses’, ‘frontal sinus’, ‘maxillary sinus’, ‘sphenoid sinus’, ‘ethmoid sinus’, in all possible combinations with the keywords ‘segmentation’ and ‘volumetric analysis’. Inclusion criteria were: articles written in English, on living human subjects, on the adult population and focused on paranasal sinuses analysis. Conclusion This article provides an overview of the types and main application of segmentation procedures on paranasal sinuses, and the results provided by the studies on this topic.

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Section: Resultsmentioning

confidence: 99%

Segmentation procedures for the assessment of paranasal sinuses volumes

et al. 2020

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“…Image processing helps us understand the acquired image data and assist the experts, saving both time and effort. With the introduction of image processing over X-ray [42,107], CT [61], and CBCT [37,39,82] images, diagnosis and treatment planning becomes easy, and the efforts of experts/radiologists are reduced. Soft X-ray with comparatively less energy is also used for imaging in agro applications.…”

Section: Imaging Techniques For Image Processingmentioning

confidence: 99%

Current research opportunities of image processing and computer vision

Gupta

2019

csci

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Image processing and computer vision is an important and essential area in today’s scenario. Several problems can be solved through computer vision techniques. There are a large number of challenges and opportunities which require skills in the field of computer vision to address them. Computer vision applications cover each band of the electromagnetic spectrum and there are numerous applications in every band. This article is targeted to the research students, scholars and researchers who are interested to solve the problems in the field of image processing and computer vision. It addresses the opportunities and current trends of computer vision applications in all emerging domains. The research needs are identified through available literature survey and classified in the corresponding domains. The possible exemplary images are collected from the different repositories available for research and shown in this paper. The opportunities mentioned in this paper are explained through the images so that a naive researcher can understand it well before proceeding to solve the corresponding problems. The databases mentioned in this article could be useful for researchers who are interested in further solving the problem. The motivation of the article is to expose the current opportunities in the field of image processing and computer vision along with corresponding repositories. Interested researchers who are working in the field can choose a problem through this article and can get the experimental images through the cited references for working further.

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“…Studies have also proposed fully automatic sophisticated and hybrid image segmentation algorithms for the segmentation of the PAS. However they offer limited value based on either insufficient accuracy, fixed thresholding, localization of seed points through manual intervention, manual VOI selection, dependency on image orientation or failure of the algorithm across variable scanning parameters [ [12][17][18] [19]].…”

Section: Introductionmentioning

confidence: 99%