Computer Assisted Detection of Polycystic Ovary Morphology in Ultrasound Images

2007 ◽  
Author(s):  
Maryruth J. Lawrence ◽  
Mark G. Eramian ◽  
Roger A. Pierson ◽  
Eric Neufeld
Keyword(s):  
Polycystic Ovary ◽  
Computer Assisted ◽  
Ultrasound Images ◽  
Computer Assisted Detection

scholarly journals Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs

2021 ◽  
Vol 11 (13) ◽  
pp. 5850
Author(s):  
Kim-Cuong T. Nguyen ◽  
Yuening Yan ◽  
Neelambar R. Kaipatur ◽  
Paul W. Major ◽  
Edmond H. Lou ◽  
...  
Keyword(s):  
Health Assessment ◽  
Computer Assisted ◽  
Ultrasound Images ◽  
Image Preprocessing ◽  
Human Volunteers ◽  
Computer Assisted Detection ◽  
The Mean ◽  
Bounding Boxes ◽  
Clinical Measurements ◽  
Dental Professionals

The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care.

scholarly journals Automated and Computer-Assisted Detection, Classification, and Diagnosis of Diabetic Retinopathy

2020 ◽  
Vol 26 (4) ◽  
pp. 544-550 ◽  
Author(s):  
Michael D. Abràmoff ◽  
Theodore Leng ◽  
Daniel S.W. Ting ◽  
Kyu Rhee ◽  
Mark B. Horton ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Computer Assisted ◽  
Computer Assisted Detection

scholarly journals Denoising of Medical Ultrasound Images using Wavelet Transform with Bilateral Filter

2019 ◽  
Vol 8 (4) ◽  
pp. 8113-8116
Keyword(s):  
Wavelet Transform ◽  
Bilateral Filter ◽  
Intrinsic Noise ◽  
Speckle Noise ◽  
Computer Assisted ◽  
Ultrasound Images ◽  
Medical Ultrasound ◽  
Edge Preservation ◽  
Neighborhood Relationship ◽  
Speckle Filtering

Medical image degradation contains a significant impact on image quality and therefore affects the human interpretation and also the accuracy of computer assisted diagnostics techniques, unfortunately ultrasound images are principally degraded by an intrinsic noise known as speckle noise. Therefore, de- speckle filtering may be pre-processing step in medical ultrasound images. During this paper we propose a new image de-noising technique is the combination of bilateral filter and wavelet transform. The main contribution of this paper is within the use of a new neighborhood relationship to develop a new multi-scale bilateral filter. Experimental outcomes validate the usefulness and also the correctness of the proposed filter in edge preservation and speckle noise reduction for medical ultrasound images.

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