Content-based image retrieval has been applied to many different biomedical applications. In almost all cases, retrievals involve a single query image of a particular modality and retrieved images are from this same modality. For example, one system may retrieve color images from eye exams, while another retrieves fMRI images of the brain. Yet real patients often have had tests from multiple di...

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the...

Background With rapid advances in technology, wearable devices as head-mounted display (HMD) have been adopted for various uses in medical science, ranging from simply aiding in fitness to assisting surgery. We aimed to investigate the feasibility and practicability of a low-cost multimodal HMD system in neuroendoscopic surgery. Methods A multimodal HMD system, mainly consisted of a HMD with ...

In this demonstration we present the Khresmoi medical search and access system. The system uses a component based architecture housed in the cloud to support target users medical information needs. This includes web systems, computer applications and mobile applications to support the multilingual and multimodal information needs of three test target groups: the general public, general practiti...

In medical imaging uncertainty is widely present in data, because of the noise in acquisition and of the partial volume effects originating from the low resolution of sensors. In particular, borders between tissues are not exactly defined and memberships in the boundary regions are intrinsically fuzzy. Therefore, computer assisted unsupervised fuzzy clustering methods turn out to be particularl...

Multimodal medical image fusion helps to increase efficiency in medical diagnosis. This paper presents multimodal medical image fusion by selecting relevant features using Principle Component Analysis (PCA) and Particle Swarm Optimization techniques (PSO). DTCWT is used for decomposition of the images into low and high frequency coefficients. Fusion rules such as combination of minimum, maximum...

In this paper, a new segmentation technique for multivalued images is elaborated. The technique makes use of the first fundamental form to access edge information of a multivalued image. On the obtained edge map, a watershedbased algorithm is applied. In order to remove noise or local texture, before segmentation, an anisotropic diffusion filter is applied, also making use of the first fundamen...

Our main goal in this paper is to produce a method for the automated segmentation of an abnormality in a medical image, including acquiring first image data representative of the medical image; locating a suspicious site at which the abnormality may exist; establishing a selection point within the suspicious site; and preprocessing the suspicious site with a constraint function to produce secon...

The paper describes the key component of the Multimodal Cell Analysis approach, a novel cytologic evaluation method for early cancer detection. The approach is based on repeated staining of a cell smear. The correlation of features and data extracted from the different stains, and related to relocated individual cells, may yield a dramatic increase of diagnostic reliability. In order to utilise...

The paper describes the key component of the Multimodal Cell Analysis approach, a novel cytologic evaluation method for early cancer detection. The approach is based on a repeated staining of a cell smear. The correlation of features and data extracted from different stainings, and related to relocated individual cells, will yield a dramatic increase of diagnostic reliability. The necessary ful...