Interpretation of Mammogram Images and Shape Description Analysis with Convex Hull Method
Kumara Guru Diderot P1, N Vasudevan2
1Kumara Guru Diderot P, Research Scholar, Hindustan Institute of Technology & Science, Chennai, (Tamil Nadu), India.
2N Vasudevan, Professor, Hindustan Institute of Technology & Science, Chennai, (Tamil Nadu), India..
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 675-681 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2755037619/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Identifying tumour within multiple areas in an image and its morphological feature is one of pioneering areas of mammogram research. Hence, this work interprets the inner shape and features of each mammogram affected regions. The scaling method deployed in this work uses odd series scan which calculates the local connected fractal components with minimal and maximal dimensions. Each image with varying extent of tumour size has been quantitatively scaled in terms of pixel level associating it with its geometrical components. The samples taken for this analysis are being measured with the following affinity of the spatial features and tumour along with the corresponding views. The irregular volume geometry is being converted to fractal dimension using box counting method. Fractal Dimension in Mammogram Images using Convex Hull method (FDMICH) algorithm does not treat the whole image as a single fractal but uses the affected region for quantitative analysis.
Keywords: Fractal Dimensions, Computational Geometry and Mammogram..
Scope of the Article: Analysis of Algorithms and Computational Complexity