ProjectHashingForests

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Hashing forests for morphological search and retrieval in neuroscientific image databases

Hashing forests for morphological search and retrieval in neuroscientific image databases

Scientific Director: Nassir Navab

Contact Person(s): Sailesh Conjeti, Amin Katouzian ,

Keywords: Machine Learning for Medical Applications

Abstract

In this project, for the first time, we propose a data-driven search and retrieval (hashing) technique for large neuron image databases. The presented method is established upon hashing forests, where multiple unsupervised random trees are used to encode neurons by parsing the neuromorphological feature space into balanced subspaces. We introduce an inverse coding formulation for retrieval of relevant neurons to effectively mitigate the need for pairwise comparisons across the database. Experimental validations show the superiority of our proposed technique over the state-of-the art methods, in terms of recall for a particular code size. This demonstrates the potential of this approach for effective morphology preserving encoding and retrieval in large neuron databases.

Team

Contact Person(s)

Amin Katouzian
Dr. Amin Katouzian
Sailesh Conjeti
Sailesh Conjeti

Working Group

Amin Katouzian
Dr. Amin Katouzian
Nassir Navab
Prof. Dr. Nassir Navab
Sailesh Conjeti
Sailesh Conjeti

Location



Technische Universität München
Institut für Informatik / I16
Boltzmannstr. 3
85748 Garching bei München

Tel.: +49 89 289-17058
Fax: +49 89 289-17059
Visit our lab at Garching.



internal project page

Please contact Sailesh Conjeti, Amin Katouzian , for available student projects within this research project.

Edit | Attach | Refresh | Diffs | More | Revision r1.1 - 04 Aug 2015 - 14:52 - SaileshConjeti

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