Applications of Computational Topology to immunohistochemistory
Project/Area Number |
15KT0100
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 特設分野 |
Research Field |
Mathematical Sciences in Search of New Cooperation
|
Research Institution | Asahikawa Medical College |
Principal Investigator |
|
Co-Investigator(Renkei-kenkyūsha) |
Takiyama Akihiro 北海道文教大学, 人間科学部, 教授 (00374520)
Kamiya Takeshi 琉球大学, 医学部, 講師 (70640647)
|
Project Period (FY) |
2015-07-10 – 2018-03-31
|
Project Status |
Completed (Fiscal Year 2017)
|
Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
Keywords | 応用数学 / 計算ホモロジー / 計量病理学 / 計算トポロジー / 病理形態学 |
Outline of Final Research Achievements |
From a viewpoint of evidence-based medicine, the systematic way of quantitative measurements have attracted interests in medical imaging processing. Focusing on the topological features of medical images, we present a methodology using computational homology for quantitative measurements in collaboration with diagnostic doctors. Our research consists of two folds: First, we apply computation of cubical homology to a micro-CT dataset of tendon graft model in rabbits to investigate the connectivity of bone trabecular. The Betti numbers are useful in the stereological description for topological feature of sponge like structures. Second, we propose a quantitative evaluation method for immunohistochemical labeling based on persistent homology. Using the pathological image data of invasive ductal carcinoma of the breast, we investigated the correlation between the newly defined persistent homology-derived index and the traditional visual scoring of nuclear grade and Ki-67 labeling index.
|
Report
(4 results)
Research Products
(15 results)