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This paper presents a new method to automatically detect occluded vehicle in semi or deep shadow areas using combined very high resolution (VHR) 3D LIDAR and hyperspectral data. The proposed shape/spectral integration (SSI) decision fusion algorithm was shown to outperform the spectral based anomaly algorithm mainly in deep shadow areas. The fusion of LIDAR DSM data with spectral data is useful in the detection of vehicles in semi and deep shadow areas. The utility of shape information was shown to be a way to enhance spectral target detection in complex urban scene.

In an effort to overcome the limitations of small target detection in complex urban scene, complementary data sets are combined to provide additional insight about a particular scene. This paper presents a method based on shape/spectral integration (SSI) decision level fusion algorithm to improve the detection of vehicles in semi and deep shadow areas. A four steps process combines high resolution LIDAR and hyperspectral data to classify shadow areas, segment vehicles in LIDAR data, detect spectral anomalies and improves vehicle detection. The SSI decision level fusion algorithm was shown to outperform detection using a single data set and the utility of shape information was shown to be a way to enhance spectral target detection in complex urban scenes.

AIMS: The aims of the study were to study the effect of pre-operative treatment on the expression of tumour-related proteins and to correlate the expression of these proteins with response and survival of patients with advanced rectal cancer. MATERIALS AND METHODS: Tissue micro-arrays from pre- and post-treatment biopsies of 99 patients with rectal cancer treated with pre-operative (chemo)radiotherapy were stained for epidermal growth factor receptor (EGFR), carbonic anhydrase IX, Ki67, vascular endothelial growth factor, cyclo-oxygenase 2 (COX-2) and cleaved cytokeratin 18 (c-CK18). Also, fibro-inflammatory alterations after treatment were evaluated. RESULTS: Pre-operative (chemo)radiotherapy caused fibro-inflammatory changes, a downregulation of proliferation (Ki67) and EGFR and an upregulation of apoptosis (cleaved CK18). Patients with a good regression during pre-operative treatment showed less proliferating and apoptotic cells in the resection specimen. Multivariate analysis showed that T downstaging, fibro-inflammatory changes in the resection specimen and COX-2 expression in the biopsy correlated with overall survival. CONCLUSIONS: Pre-operative treatment has an effect on proliferation, apoptosis, inflammation and EGFR expression. The classical clinical parameters as well as fibro-inflammatory changes and COX-2 expression seem most valuable as predictors for survival.

An approach is presented to the long range automatic detection of vehicles, using multisensor image sequences. The method is tested on a database of multispectral image sequences, acquired under diverse operational conditions. The approach consists of two parts. The first part uses a semisupervised approach, based on texture parameters, for detecting stationary targets. For each type of sensor one learning image is chosen. Texture parameters are calculated at each pixel of the learning images and are combined using logistic regression into a value that represents the conditional probability that the pixel belongs to a target given the texture parameters. The actual detection algorithm applies the same combination to the texture features calculated on the remainder of the database (test images). When the results of this feature-level fusion are stored as an image, the local maxima correspond to likely target positions. These feature-level-fused images are calculated for each sensor. In a sensor fusion step, the results obtained per sensor are then combined again. Region growing around the local maxima is then used to detect the targets. The second part of the algorithm searches for moving targets. To detect moving vehicles, any motion of the sensor must be detected first. If sensor motion is detected, it is estimated using a Markov random field model. Available prior knowledge about the sensor motion is used to simplify the motion estimation. The estimate is used to warp past images onto the current image in a temporal fusion approach and moving targets are detected by thresholding the difference between the original and warped images. Decision level fusion combines the results from both parts of the algorithm. © 1993 Society of Photo-Optical Instrumentation Engineers., SCOPUS: ar.j, info:eu-repo/semantics/published