نتائج البحث

Development and validation of the surmising model for volumetric breast density using X-ray exposure conditions in digital mammography.

• Authors : Yamamuro, Mika¹ (AUTHOR); Asai, Yoshiyuki¹ (AUTHOR) ; Yamada, Takahiro² (AUTHOR)

Subjects: *TIME series analysis; DIGITAL mammography; BREAST

• Source: Medical & Biological Engineering & Computing. Jan2025, Vol. 63 Issue 1, p169-179. 11p.

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Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment.

• Authors : Tan, Maxine^1,2 ; Al-Shabi, Mundher¹; Chan, Wai Yee³

Subjects: MAMMOGRAMS; DIGITAL mammography; TOMOSYNTHESIS

• Source: Medical & Biological Engineering & Computing. Feb2021, Vol. 59 Issue 2, p355-367. 13p. 3 Black and White Photographs, 5 Charts, 2 Graphs.

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Breast Cancer Detection based on 3-D Mammography Images using Deep Learning Strategies.

• Authors : Sagayam, K. Martin¹ ; Anton Jone, A. Amir¹ ; Cengiz, Korhan²

Subjects: *ARTIFICIAL neural networks; BREAST cancer diagnosis; DEEP learning

• Source: Journal of Information Technology Management (JITM). 2022, Vol. 14 Issue 4, p2-18. 17p.

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Quantitative assessment of microcalcification cluster image quality in digital breast tomosynthesis, 2-dimensional and synthetic mammography.

• Authors : Petropoulos, Andreas E.¹; Skiadopoulos, Spyros G.¹; Karahaliou, Anna N.¹

Subjects: CALCIFICATIONS of the breast; TOMOSYNTHESIS; MAMMOGRAMS

• Source: Medical & Biological Engineering & Computing. Jan2020, Vol. 58 Issue 1, p187-209. 23p. 6 Diagrams, 11 Charts, 5 Graphs.

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Learning multi-frequency features in convolutional network for mammography classification.

• Authors : Wang, Yiming¹ (AUTHOR); Qi, Yunliang¹ (AUTHOR); Xu, Chunbo¹ (AUTHOR)

• Source: Medical & Biological Engineering & Computing. Jul2022, Vol. 60 Issue 7, p2051-2062. 12p. 3 Color Photographs, 4 Diagrams, 3 Charts, 4 Graphs.

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A New Image Mining Approach for Detecting Micro-Calcification in Digital Mammograms.

• Authors : Moradkhani, Farzaneh¹ (AUTHOR); Bigham, Bahram Sadeghi² (AUTHOR)

Subjects: *DATA mining; DIGITAL mammography; IMAGE analysis

• Source: Applied Artificial Intelligence. 2017, Vol. 31 Issue 5/6, p411-424. 14p.

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Development of intuitionistic fuzzy special embedded convolutional neural network for mammography enhancement.

• Authors : Kr Ghosh, Swarup¹ (AUTHOR) ; Biswas, Biswajit² (AUTHOR); Ghosh, Anupam³ (AUTHOR)

Subjects: CONVOLUTIONAL neural networks; X-ray imaging; MAMMOGRAMS

• Source: Computational Intelligence. Feb2021, Vol. 37 Issue 1, p47-69. 23p.

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Prediction of glandularity and breast radiation dose from mammography results in Japanese women.

• Authors : Yamamuro, Mika¹ ; Asai, Yoshiyuki¹ ; Yamada, Koji¹

Subjects: *REGRESSION analysis; RADIATION doses; BODY weightJAPAN

• Source: Medical & Biological Engineering & Computing. Jan2019, Vol. 57 Issue 1, p289-298. 10p. 4 Diagrams, 3 Charts, 6 Graphs.

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Computer-aided classification of breast masses in mammogram images based on spherical wavelet transform and support vector machines.

• Authors : Görgel, Pelin¹ ; Sertbas, Ahmet¹; Uçan, Osman Nuri²

Subjects: MAMMOGRAMS; DIGITAL mammography; BREAST disease diagnosis

• Source: Expert Systems. Feb2015, Vol. 32 Issue 1, p155-164. 10p.

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Microcontrolled pyro-electric instrument for measuring X-ray intensity in mammography.

• Authors : De Paula, M. H.¹; De Carvalho, A. A.² ; Brassalotti, A. L.²

Subjects: *MATHEMATICAL models; *RESEARCH; *PRODUCT design

• Source: Medical & Biological Engineering & Computing. Nov2005, Vol. 43 Issue 6, p751-755. 5p.

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