Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
533870 | Pattern Recognition Letters | 2014 | 8 Pages |
•Attribute based descriptors of synaptic junctions in Electron Micrographs.•Proposed descriptors are low dimensional and scalable.•Investigation of feature fusion for detecting co-occurring attributes.•Large scale experiments on synapse classification/detection.
Classification and detection of biological structures in Electron Micrographs (EM) is a relatively new large scale image analysis problem. The primary challenges are in modeling diverse visual characteristics and development of scalable techniques. In this paper we propose novel methods for synapse detection and localization, an important problem in connectomics. We first propose an attribute based descriptor for characterizing synaptic junctions. These descriptors are task specific, low dimensional and can be scaled across large image sizes. Subsequently, techniques for fast localization of these junctions are proposed. Experimental results on images acquired from a mammalian retinal tissue compare favorably with state of the art descriptors used for object detection.