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Enhancing Global Access: interview with CZI grantee Paul Hernandez

Posted by , on 24 January 2024

ADVANCING BIOIMAGING CORE SERVICES WITH ARTIFICIAL INTELLIGENCE Paul Hernandez is a mathematician who develops algorithms for image analysis. Currently, he is pioneering the use of machine learning and deep learning techniques for image analysis. He is an imaging scientist awardee of the CZI cycle 2 call. His project aims to develop accurate and high-throughput AI
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Enhancing Global Access: interview with CZI grantee Federico Lecumberry

Posted by , on 24 January 2024

BIOIMAGE ACQUISITION AND PROCESSING CORE: BUILDING SKILLS IN BIOMEDICINE Federico Lecumberry is a professor at the Faculty of Engineering at Universidad de la República in Uruguay. Their project, called IMAGINA, aims to develop the community’s skillset in computational bioimaging processing and analysis software, and develop original novel algorithms and software for imaging. Through their work
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Enhancing Global Access: interview with CZI grantee Uri Manor

Posted by , on 24 January 2024

OPEN DISSEMINATION OF NOVEL IMAGING TOOLS FOR THE RESEARCH COMMUNITY Uri Manor is an imaging scientist with a background in cell biology and computational methods. His project focuses on building new probes to improve and accelerate research, and on using artificial intelligence to break barriers in the way we do microscopy.  What was the inspiration
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Enhancing Global Access: interview with CZI grantee Beth Cimini

Posted by , on 24 January 2024

COLLABORATING ON CUSTOMIZED IMAGE ANALYSIS AND COMMUNITY ENGAGEMENT Beth Cimini is the Associate Director for Bioimage Analysis for the Imaging Platform at the Broad Institute of MIT and Harvard, where together with her team she directs efforts of software engineering including tools such as CellProfiler, researching morphological profiling and developing imaging assays. Her efforts also
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Enhancing Global Access: interview with CZI grantee Thierry Pecot

Posted by , on 24 January 2024

BRINGING ARTIFICIAL INTELLIGENCE TO BIOLOGISTS Thierry Pécot is an engineer and applied mathematician who develops deep learning frameworks for a variety of applications. As his project for the Cycle 1 imaging scientist call, Thierry Pécot proposed enabling biologists to apply deep learning tools to their own images. He interacts with biologists to identify the needs required to develop deep
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Microscopy preprints – bioimage analysis tools

Posted by , on 29 December 2023

Here is a curated selection of preprints published recently. In this post, we focus specifically on new tools for bioimage analysis and data management released up until 20 December.
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Crick Bioimage Analysis Symposium 2023 - a Review

Posted by , on 22 December 2023

(By Vanessa Dao, Hradini Konthalapalli, Olatz Niembro Vivanco, Karishma Valand) The Crick Bioimage Analysis Symposium had its first in-person meeting in 2022. This year, #CBIAS2023 gathered around 200 people on site and 80 virtually. It has been an exciting two days of bringing biomedical researchers and their questions together with image analysis and their techniques.
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An interview with Laura Daza

Posted by , on 28 November 2023

MiniBio: Laura Daza just finished her PhD at CinfonIA, at Universidad de los Andes in Colombia. During her doctorate degree, she has worked in a variety of projects ranging from Computer Vision to image and data analysis. She studied Biomedical Engineering at Universidad de los Andes, where she first found her passion for Image Analysis.
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Microscopy preprints – bioimage analysis tools

Posted by , on 17 November 2023

Here is a curated selection of preprints published recently. In this post, we focus specifically on new tools for bioimage analysis and data management.
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Analyzing calcium imaging data using Python

Posted by , on 27 October 2023

Andrey AndreevCalifornia Institute of Technology, David Prober labaandreev@caltech.edu Calcium imaging allows tracking neural activity in time with single-cell resolution. There are many questions you might be interested in answering using this technique: which cells are tuned to the stimuli? is there periodic activity present in the data? which cells act together? how complex is the activity
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