scholarly journals Modified Differential Box Counting in Breast Masses for Bioinformatics Applications

2022 ◽  
Vol 70 (2) ◽  
pp. 3049-3066
Author(s):  
S. Sathiya Devi ◽  
S. Vidivelli
Keyword(s):  
Breast Masses ◽  
Box Counting

3D box-counting algorithm for calculating fractal dimension of cities

2010 ◽  
Vol 30 (8) ◽  
pp. 2070-2072
Author(s):  
Le-shan ZHANG ◽  
Ge CHEN ◽  
Yong HAN ◽  
Tao ZHANG
Keyword(s):  
Fractal Dimension ◽  
Box Counting ◽  
Counting Algorithm

Clinical Application of Computer-Aided Diagnosis According to S-Detect in Category 4 Breast Lesions: Prospective Single-Center Study (Preprint)

2020 ◽  
Author(s):  
Pengfei Sun ◽  
Chen Chen ◽  
Weiqi Wang ◽  
Lei Liang ◽  
Dan Luo ◽  
...  
Keyword(s):  
Clinical Management ◽  
Diagnostic Performance ◽  
Breast Biopsy ◽  
Computer Aided Diagnosis ◽  
Breast Lesions ◽  
Breast Masses ◽  
Computer Aided ◽  
Conventional Ultrasound ◽  
Us Findings ◽  
Aided Diagnosis

BACKGROUND Computer-aided diagnosis (CAD) is a useful tool that can provide a reference for the differential diagnosis of benign and malignant breast lesion. Previous studies have demonstrated that CAD can improve the diagnostic performance. However, conventional ultrasound (US) combined with CAD were used to adjust the classification of category 4 lesions has been few assessed. OBJECTIVE The objective of our study was to evaluate the diagnosis performance of conventional ultrasound combined with a CAD system S-Detect in the category of BI-RADS 4 breast lesions. METHODS Between December 2018 and May 2020, we enrolled patients in this study who received conventional ultrasound and S-Detect before US-guided biopsy or surgical excision. The diagnostic performance was compared between US findings only and the combined use of US findings with S-Detect, which were correlated with pathology results. RESULTS A total of 98 patients (mean age 51.06 ±16.25 years, range 22-81) with 110 breast masses (mean size1.97±1.38cm, range0.6-8.5) were included in this study. Of the 110 breast masses, 64/110 (58.18%) were benign, 46/110 (41.82%) were malignant. Compared with conventional ultrasound, a significant increase in specificity (0% to 53.12%, P<.001), accuracy (41.81% to70.19%, P<.001) were noted, with no statistically significant decrease on sensitivity(100% to 95.65% ,P=.48). According to S-Detect-guided US BI-RADS re-classification, 30 out of 110 (27.27%) breast lesions underwent a correct change in clinical management, 74of 110 (67.27%) breast lesions underwent no change and 6 of 110 (5.45%) breast lesions underwent an incorrect change in clinical management. The biopsy rate decreased from 100% to 67.27 % (P<.001).Benign masses among subcategory 4a had higher rates of possibly benign assessment on S-Detect for the US only (60% to 0%, P<.001). CONCLUSIONS S-Detect can be used as an additional diagnostic tool to improve the specificity and accuracy in clinical practice. S-Detect have the potential to be used in downgrading benign masses misclassified as BI-RADS category 4 on US by radiologist, and may reduce unnecessary breast biopsy. CLINICALTRIAL none

scholarly journals Supramolecular Fractal Growth of Self-Assembled Fibrillar Networks

Gels ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 46
Author(s):  
Pedram Nasr ◽  
Hannah Leung ◽  
France-Isabelle Auzanneau ◽  
Michael A. Rogers
Keyword(s):  
Fractal Dimension ◽  
Crystallization Temperature ◽  
Cayley Tree ◽  
Fractal Dimensions ◽  
Self Similarity ◽  
Avrami Model ◽  
Cluster Aggregation ◽  
Box Counting ◽  
Self Assembled ◽  
Limited Diffusion

Complex morphologies, as is the case in self-assembled fibrillar networks (SAFiNs) of 1,3:2,4-Dibenzylidene sorbitol (DBS), are often characterized by their Fractal dimension and not Euclidean. Self-similarity presents for DBS-polyethylene glycol (PEG) SAFiNs in the Cayley Tree branching pattern, similar box-counting fractal dimensions across length scales, and fractals derived from the Avrami model. Irrespective of the crystallization temperature, fractal values corresponded to limited diffusion aggregation and not ballistic particle–cluster aggregation. Additionally, the fractal dimension of the SAFiN was affected more by changes in solvent viscosity (e.g., PEG200 compared to PEG600) than crystallization temperature. Most surprising was the evidence of Cayley branching not only for the radial fibers within the spherulitic but also on the fiber surfaces.

scholarly journals Imaging Evaluation of Male Breast Masses with Histopathologic Correlation: A Case Series

2021 ◽  
Author(s):  
Tanvi P. Vaidya ◽  
Subhash K. Ramani
Keyword(s):  
Magnetic Resonance Imaging ◽  
Wide Spectrum ◽  
Case Series ◽  
Male Breast ◽  
Radiological Evaluation ◽  
Resonance Imaging ◽  
Imaging Evaluation ◽  
Breast Masses ◽  
Female Breast

AbstractThe male breast can be afflicted with a wide spectrum of benign and malignant masses, similar to the female breast. A systematic radiological evaluation using mammography, ultrasonography, and when appropriate, magnetic resonance imaging, could aid this differentiation and provide clues to the diagnosis. In this article, we present six cases of male breast masses with an emphasis on the role of imaging in characterization and diagnosis.

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