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PyIFT: image processing using image foresting transform in Python

Grant number: 18/08951-8
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2018
Effective date (End): May 31, 2019
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Alexandre Xavier Falcão
Grantee:Jordão Okuma Barbosa Ferraz Bragantini
Home Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?, AP.TEM

Abstract

Python is an interpreted language that, thanks to the help of communities around the world, can be used for scientific applications, with most of these toolboxes being additional computational methods. This project aims to create a Python toolbox, called PyIFT, for image processing and analysis using the Image-Forest Transform, thus taking advantage of Python's dynamic typing to perform tests and aid in teaching and research. As some algorithms involving the Image-Forest Transformation are interactive, this toolbox will include tools for interaction of methods with users, visualization of propagation of paths and labels (colors) of forest trees, facilitating understanding, and integration with other modules Python used by the research group.

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MARTINS, SAMUEL BOTTER; BRAGANTINI, JORDAO; FALCAO, ALEXANDRE XAVIER; YASUDA, CLARISSA LIN. An adaptive probabilistic atlas for anomalous brain segmentation in MR images. Medical Physics, v. 46, n. 11, p. 4940-4950, NOV 2019. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.