Automatic Cell Tracking and Kinetic Feature Description of Cell Paths for Image Mining

2015 ◽  
pp. 441-451
Author(s):  
Petra Perner
Keyword(s):  
Cell Tracking ◽  
Image Mining ◽  
Kinetic Feature ◽  
Feature Description

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

Automated Feature Description of Renal Size Using Image Processing

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Nur Farhana Rosli ◽  
◽  
Musab Sahrim ◽  
Wan Zakiah Wan Ismail ◽  
Irneza Ismail ◽  
...  
Keyword(s):  
Image Processing ◽  
Feature Description ◽  
Renal Size

Image Segmentationand Intelligent Algorithms for Cell Tracking

2016 ◽  
Vol 6 (2) ◽  
pp. 199-216
Author(s):  
Safaai Bin Deris ◽  
Nazar Zaki
Keyword(s):  
Cell Tracking ◽  
Intelligent Algorithms

Massive picture retrieval system based on big data image mining

2021 ◽  
Vol 121 ◽  
pp. 54-58
Author(s):  
Kun Zhang ◽  
Kai Chen ◽  
Binghui Fan
Keyword(s):  
Big Data ◽  
Retrieval System ◽  
Image Mining

scholarly journals Optical and genetic tools for in vivo single cell tracking

2021 ◽  
Vol 358 ◽  
pp. 109192
Author(s):  
Yajie Liang ◽  
Liset M. de la Prida
Keyword(s):  
Single Cell ◽  
Cell Tracking ◽  
Genetic Tools

scholarly journals Allogeneic human neural stem cells for improved therapeutic delivery to peritoneal ovarian cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rachael Mooney ◽  
Wafa Abidi ◽  
Jennifer Batalla-Covello ◽  
Hoi Wa Ngai ◽  
Caitlyn Hyde ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cell Tracking ◽  
Scale Up ◽  
Cancer Therapeutics ◽  
Cost Effective ◽  
Tumor Stroma ◽  
Clinical Safety ◽  
Peritoneal Cancer ◽  
Human Neural Stem Cells ◽  
Link Type

Abstract Background Immortalized, clonal HB1.F3.CD21 human neural stem/progenitor cells (NSCs), loaded with therapeutic cargo prior to intraperitoneal (IP) injection, have been shown to improve the delivery and efficacy of therapeutic agents in pre-clinical models of stage III ovarian cancer. In previous studies, the distribution and efficacy of the NSC-delivered cargo has been examined; however, the fate of the NSCs has not yet been explored. Methods To monitor NSC tropism, we used an unconventional method of quantifying endocytosed gold nanorods to overcome the weaknesses of existing cell-tracking technologies. Results Here, we report efficient tumor tropism of HB1.F3.CD21 NSCs, showing that they primarily distribute to the tumor stroma surrounding individual tumor foci within 3 h after injection, reaching up to 95% of IP metastases without localizing to healthy tissue. Furthermore, we demonstrate that these NSCs are non-tumorigenic and non-immunogenic within the peritoneal setting. Conclusions Their efficient tropism, combined with their promising clinical safety features and potential for cost-effective scale-up, positions this NSC line as a practical, off-the-shelf platform to improve the delivery of a myriad of peritoneal cancer therapeutics.

Non-radioactive imaging strategies for in vivo immune cell tracking

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Łukasz Kiraga ◽  
Paulina Kucharzewska ◽  
Damian Strzemecki ◽  
Tomasz P. Rygiel ◽  
Magdalena Król
Keyword(s):  
Diagnostic Imaging ◽  
Contrast Agents ◽  
Cell Tracking ◽  
Immune Cell ◽  
Imaging Techniques ◽  
Diagnostic Technique ◽  
Cell Labeling ◽  
X Ray Imaging ◽  
Disease Study

Abstract In vivo tracking of administered cells chosen for specific disease treatment may be conducted by diagnostic imaging techniques preceded by cell labeling with special contrast agents. The most commonly used agents are those with radioactive properties, however their use in research is often impossible. This review paper focuses on the essential aspect of cell tracking with the exclusion of radioisotope tracers, therefore we compare application of different types of non-radioactive contrast agents (cell tracers), methods of cell labeling and application of various techniques for cell tracking, which are commonly used in preclinical or clinical studies. We discuss diagnostic imaging methods belonging to three groups: (1) Contrast-enhanced X-ray imaging, (2) Magnetic resonance imaging, and (3) Optical imaging. In addition, we present some interesting data from our own research on tracking immune cell with the use of discussed methods. Finally, we introduce an algorithm which may be useful for researchers planning leukocyte targeting studies, which may help to choose the appropriate cell type, contrast agent and diagnostic technique for particular disease study.

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