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Albert Cardona
Researcher at University of Cambridge
Publications - 124
Citations - 52747
Albert Cardona is an academic researcher from University of Cambridge. The author has contributed to research in topics: Neuropil & Connectome. The author has an hindex of 39, co-authored 115 publications receiving 37644 citations. Previous affiliations of Albert Cardona include University of Zurich & Max Planck Society.
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Journal ArticleDOI
Fiji: an open-source platform for biological-image analysis
Johannes Schindelin,Ignacio Arganda-Carreras,Erwin Frise,Verena Kaynig,Mark Longair,Tobias Pietzsch,Stephan Preibisch,Curtis Rueden,Stephan Saalfeld,Benjamin Schmid,Jean-Yves Tinevez,Daniel J. White,Volker Hartenstein,Kevin W. Eliceiri,Pavel Tomancak,Albert Cardona +15 more
TL;DR: Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis that facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system.
Journal ArticleDOI
Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification.
Ignacio Arganda-Carreras,Ignacio Arganda-Carreras,Verena Kaynig,Curtis Rueden,Kevin W. Eliceiri,Johannes Schindelin,Albert Cardona,H. Sebastian Seung +7 more
TL;DR: The Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically, is introduced.
Journal ArticleDOI
TrakEM2 software for neural circuit reconstruction
Albert Cardona,Stephan Saalfeld,Johannes Schindelin,Ignacio Arganda-Carreras,Stephan Preibisch,Mark Longair,Pavel Tomancak,Volker Hartenstein,Rodney J. Douglas +8 more
TL;DR: A software application, TrakEM2, is designed that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes and addresses the challenges of image volume composition from individual, deformed images.
Journal ArticleDOI
A high-level 3D visualization API for Java and ImageJ
TL;DR: This framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment and provides high-level access to volume rendering, volume editing, surface extraction, and image annotation.
Journal ArticleDOI
The complete connectome of a learning and memory centre in an insect brain
Katharina Eichler,Feng Li,Ashok Litwin-Kumar,Youngser Park,Ingrid Andrade,Casey M Schneider-Mizell,Timo Saumweber,Annina Huser,Claire Eschbach,Bertram Gerber,Bertram Gerber,Richard D. Fetter,James W Truman,Carey E. Priebe,Larry F. Abbott,Andreas S. Thum,Marta Zlatic,Marta Zlatic,Albert Cardona,Albert Cardona +19 more
TL;DR: It is found that most Kenyon cells integrate random combinations of inputs but that a subset receives stereotyped inputs from single projection neurons, which maximizes performance of a model output neuron on a stimulus discrimination task.