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Ana Maria do Carmo

dblp:311/3089 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0009-0005-1015-4323ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 56% Medical and health informatics · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › medical imaging › medical image analysis
medical image segmentation
0.612022
PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images · Bioinform. 2022
Bioinformatics and computational biology › bioimage informatics › bioimage analysis
microscopy image analysis
0.612022
PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images · Bioinform. 2022
Bioinformatics and computational biology
cell biology
0.212022
PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images · Bioinform. 2022

Methods — techniques the papers use, named apart from their topics

watershed · 0.6machine learning-based segmentation · 0.6
YearPublicationVenuePosition
2022 PyJAMAS: open-source, multimodal segmentation and analysis of microscopy images
abstract
SUMMARY: Our increasing ability to resolve fine details using light microscopy is matched by an increasing need to quantify images in order to detect and measure phenotypes. Despite their central role in cell biology, many image analysis tools require a financial investment, are released as proprietary software, or are implemented in languages not friendly for beginners, and thus are used as black boxes. To overcome these limitations, we have developed PyJAMAS, an open-source tool for image processing and analysis written in Python. PyJAMAS provides a variety of segmentation tools, including watershed and machine learning-based methods; takes advantage of Jupyter notebooks for the display and reproducibility of data analyses; and can be used through a cross-platform graphical user interface or as part of Python scripts via a comprehensive application programming interface. AVAILABILITY AND IMPLEMENTATION: PyJAMAS is open-source and available at https://bitbucket.org/rfg_lab/pyjamas. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Rodrigo Fernandez-Gonzalez, Negar Balaghi, Kelly Wang, Ray Hawkins, Katheryn Rothenberg, Christopher McFaul, Clara Schimmer, Michelle Ly, Ana Maria do Carmo, Gordana Scepanovic, Gonca Erdemci-Tandogan, Veronica Castle
Bioinform.9