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Alejandro Luis Callara

Researcher at University of Pisa

Publications -  30
Citations -  140

Alejandro Luis Callara is an academic researcher from University of Pisa. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 4, co-authored 18 publications receiving 76 citations.

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Journal ArticleDOI

Clarifying CLARITY: Quantitative Optimization of the Diffusion Based Delipidation Protocol for Genetically Labeled Tissue

TL;DR: The results show that detergent-based delipidation for more than 5 days does not increase tissue clarity but the fraction of GFP in the tissue continues to diminish, and the optimum clearing time for 1 mm-thick slices was identified as 5 days, which is the best compromise.
Journal ArticleDOI

Gotta Trace 'em All: A Mini-Review on Tools and Procedures for Segmenting Single Neurons Toward Deciphering the Structural Connectome.

TL;DR: New methods and tools for processing tissues and acquiring images at sub-cellular scales, which will require new robust algorithms for identifying neurons and their sub-structures will lead to a more detailed structural map of the brain, taking twenty-first century cellular neuroscience to the next level.
Journal ArticleDOI

A Manual Segmentation Tool for Three-Dimensional Neuron Datasets.

TL;DR: In this paper, a manual segmentation tool (ManSegTool) was developed to facilitate the manual isolation of complex objects from image stacks, such as neurons in their native arrangement within the brain, by loading an image stack, scrolling down the images and manually drawing the structures of interest stack-by-stack.
Journal ArticleDOI

Towards a Contactless Stress Classification Using Thermal Imaging

TL;DR: In this paper , the authors investigated the contribution of thermal imaging for an effective automatic stress detection with the perspective of a contactless stress recognition system, which recorded both ANS correlates (cardiac, electrodermal and respiratory activity) and thermal images from 25 volunteers under acute stress induced by the Stroop test.
Proceedings ArticleDOI

A preliminary quantitative EEG study on Augmented Reality Guidance of Manual Tasks

TL;DR: Although preliminary, EEG power results suggest that mental workload associated with AR usage may derive from enhanced difficulty associated with the task, and this work quantifies the reduction of users’ performance based on starting and end points gap errors.