Computer Aided Diagnosis of Mammographic Tissue Using Shapelets in Quaternionic Representation

Apostolopoulos, George; Koutras, Athanasios; Christoyianni, Ioanna; Dermatas, Evangelos

doi:10.1007/978-3-319-32703-7_45

Cited by 4 publications

(5 citation statements)

References 26 publications

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“…Ultrasound had greater PPV and NPV as compared to mammography [25] . Phi XA et al in a research article reported that Digital Breast Tomosynthesis has a superior sensitivity and specificity than mammography in diagnostic setting in dense breast where as an increase in cancer detection rate was noted in combining Digital Breast Tomosynthesis and Mammography in dense breast [3,8] . Similar findings were reported by Bernardi D et al in their study over 9672 screening participants [26] .…”

Section: Discussionmentioning

confidence: 99%

Utility of whole breast ultrasound and digital tomosynthesis as an adjunct with mammography in dense breast to detect breast lesions

Yadav¹,

Padmanabhan²

2019

Int. J. Radiol. Diagn. Imaging

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Mammography has been widely adopted as the primary screening tool in breast cancer detection and assessment. Screening in dense breast makes it difficult to detect lesions on screening and lowers its sensitivity to detect small lesions. Sensitivity and specificity improves with use of digital breast tomosynthesis and whole breast ultrasound in detecting lesions and also in differentiating benign and malignant breast lesions. Breast ultrasound and DBT have shown equivocal significance in detecting breast lesion on screening in the present study. The aim of the study was to evaluate utility of whole breast ultrasound and digital tomosynthesis as an adjunct with mammography in dense breast to detect breast lesions.

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Section: Discussionmentioning

confidence: 99%

Utility of whole breast ultrasound and digital tomosynthesis as an adjunct with mammography in dense breast to detect breast lesions

Yadav¹,

Padmanabhan²

2019

Int. J. Radiol. Diagn. Imaging

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“…Shapelets are generally used to seal an image based on various basic shapes 35 . There are 2 kinds of Shapelets they are (i) Cartesian and (ii) Polar.…”

Section: D Reconstruction Technique For Mri Using Shapeletsmentioning

confidence: 99%

“…There are 2 kinds of Shapelets they are (i) Cartesian and (ii) Polar. Quaternion is used to obtain 3D rotation which accumulates all information in the form of array structure by converting color image into imaginary part and completely extravagances the vector 35 . Generally, Quaternion has one real part and three imaginary parts.…”

Section: D Reconstruction Technique For Mri Using Shapeletsmentioning

confidence: 99%

“…Shapelets are generally used to seal an image based on various basic shapes. 35 There are 2 kinds of Shapelets they are (i) Cartesian and (ii) Polar. Quaternion is used to obtain 3D rotation which accumulates all information in the form of array structure by converting color image into imaginary part and completely extravagances the vector.…”

Section: D Reconstruction Technique For Mri Using Shapeletsmentioning

confidence: 99%

“…Quaternion is used to obtain 3D rotation which accumulates all information in the form of array structure by converting color image into imaginary part and completely extravagances the vector. 35 Generally, Quaternion has one real part and three imaginary parts. A quaternion is expressed in the following Equation (1).…”

Section: D Reconstruction Technique For Mri Using Shapeletsmentioning

confidence: 99%

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An affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG‐DMCA) based three dimensional image reconstruction approach

Joseph

Dennisan

2022

Int J Imaging Syst Tech

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In this manuscript, the novel three dimensional (3D) image reconstruction approach based on affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG-DMCA) is proposed. The major purpose of this manuscript is to divide the brain tumor based on Shapelets. Here, the information about the shape/depth that can be obtained in every two dimensional (2D) image on the image stack is handled to acquire a 3D reconstruction, which provides high accurate 3D view of tumor Region of Interest (ROI). Then, the 3D model is rendered with the help of the proposed Deep learned Marching Cubes Algorithm (Deep MCA) at 3D reconstruction technique. The performance of the proposed method is executed in MATLAB. The simulation results show that the proposed ISRG-DMCA algorithm attains a higher detection rate 14.117%, 5.435%, higher accuracy rate 9.556%, 26.41% and lower execution time 66.667%, 75%, compared with the existing methods, like Improved Marching Cubes Algorithm (IMCA), Improved CNN-CRF method, respectively. In the proposed ISRG-DMCA method, the volume of the tumor has a length of 2.56 mm. Finally, the simulation outcomes demonstrate that the proposed ISRG-DMCA method can be able to find the optimal solutions efficiently and accurately.

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Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors

Apostolopoulos

Koutras

Anyfantis

et al. 2021

Proceedings of the International Neural Networks Society

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Computer Aided Diagnosis of Mammographic Tissue Using Shapelets in Quaternionic Representation

Cited by 4 publications

References 26 publications

Utility of whole breast ultrasound and digital tomosynthesis as an adjunct with mammography in dense breast to detect breast lesions

Utility of whole breast ultrasound and digital tomosynthesis as an adjunct with mammography in dense breast to detect breast lesions

An affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG‐DMCA) based three dimensional image reconstruction approach

Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors

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