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SUMMARY:Image-based quantitative morphology with geometrical models - Dr V
 irginie Uhlmann from EMBL-EBI in Hinxton
DTSTART:20200217T130000Z
DTEND:20200217T140000Z
UID:TALK138202@talks.cam.ac.uk
CONTACT:Anna Toporska
DESCRIPTION:Images and video sequences are crucial sources of information 
 in experimental biology\, and quantitative bioimage analysis has grown int
 o an independent field of research. Recent advances in computer vision pro
 vide efficient learning-based tools to identify objects in images\, as wel
 l as segment and track them. Classically\, objects in an image are then de
 fined by the set of pixels or voxels that compose them\, which is ill-suit
 ed to capture many of the subtle features that are typical of biological p
 henomenon. While the process of image acquisition acts as an analog-to-dig
 ital converter\, projecting the world onto the space of image data\, geome
 trical modelling can be used to revert this effect and represent biologica
 l object from images in an “infinite resolution” way. Uhlmann group fo
 cuses on the development of such models to offer a common\, unified mathem
 atical representation of morphology\, regardless of the imaging modality. 
 Ultimately\, it allows studying phenotypic features\, as well as changes a
 nd differences thereof\, in a purely analytical way. In her talk Dr Uhlman
 n will describe the general principles behind the construction of geometri
 cal models in 2 and 3D and illustrate their use in various bioimage analys
 is problems
LOCATION:CRUK CI Lecture Theatre (Room 001)
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