Content based retrieval of 3D cellular structures
Recent advances in management of multimedia digital libraries enable effective retrieval of information in the form of audio, image and video. However, retrieval of information in the form of 3D objects has received limited attention so far. Yet many archives of 3D objects already exist and are expected to grow both in relevance and size. In this paper, we address the problem of effective description and retrieval of 3D data representing intracellular structures. These structures are represented in the form of image stacks, being an image stack a set of 2D images representing planar sections of a cellular body at different heights. In the proposed method, 2D visual feature descriptors and Hidden Markov Models are combined to obtain a representation model which is able to distinguish such intracellular structures as Golgi, nucleus, endoplasmic reticulum and lysosomes. Preliminary results are presented to show the effectiveness of the proposed representation model.