[BIC-announce] Talk today Nov 10th: 3pm to 4pm: "Characterisation of Stochastic Geometry in Microscopy"

[Siddiqi Kaleem]

BRaIN / Centre for Intelligent Machines / School of Computer Science Joint Seminar
 
 
 
 
"Characterisation of Stochastic Geometry in Microscopy"
 
 
 
Jon Sporring, PhD
 
Department of Computer Science, University of Copenhagen
 
 
 
 
Thursday November 10, 2022, 3– 4 pm
 
 
 
 
Hybrid seminar

Participation by Zoom: 
https://us06web.zoom.us/meeting/register/tZAkc-CurTgrGtQidMNR5thBC_K1dRQc45OB <https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fus06web.zoom.us%2Fmeeting%2Fregister%2FtZAkc-CurTgrGtQidMNR5thBC_K1dRQc45OB&data=05%7C01%7Cann.jack%40mcgill.ca%7C6225e446c0fc4522e2c708dac275ae05%7Ccd31967152e74a68afa9fcf8f89f09ea%7C0%7C0%7C638036107926908665%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=xgFGMOgd%2BmVHvWDFLNgkpERqBWIJTz4NDGbTLmmtEH8%3D&reserved=0>
 
In Person, McConnell Engineering 437, no registration required
 
or
 
Via Zoom – Register here to obtain zoom link <https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fus06web.zoom.us%2Fmeeting%2Fregister%2FtZAkc-CurTgrGtQidMNR5thBC_K1dRQc45OB&data=05%7C01%7Cann.jack%40mcgill.ca%7C6225e446c0fc4522e2c708dac275ae05%7Ccd31967152e74a68afa9fcf8f89f09ea%7C0%7C0%7C638036107926908665%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=xgFGMOgd%2BmVHvWDFLNgkpERqBWIJTz4NDGbTLmmtEH8%3D&reserved=0>
 
Abstract: 
Geometrical measurements of biological objects form the basis of many quantitative analyses. Hausdorff measures such as the volume and the area of objects are simple and popular descriptors of individual objects; however, for most biological processes, the interaction between objects cannot be ignored,and the shape and function of neighboring objects are mutually influential. We present a theory on the geometrical interaction between objects inspired by K-functions for spatial point-processes. Our theory describes the relation between two objects: a reference and an observed object. We generate the r-parallel sets of the reference object, calculate the intersection between the r-parallel sets and the observed object, and define measures on these intersections. The measures are simple, like the volume or surface area, but describe further details about the shape of individual objects and their pairwise geometrical relation. 
 
 

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