Publications by Costantino Grana

Objective: To characterize the microscopic aspects of the dermoscopic pigment network in vivo, by means of confocal scanning laser microscopy. Design: Confocal imaging was performed on melanocytic lesions characterized by pigment network at dermoscopy. Some confocal architectural and cytologic features, as observed at the dermoepidermal junction, were morphologically described and quantified by means of a dedicated program. Setting: University medical department. Study Population: We studied confocal images of 15 melanomas, 15 dermoscopic atypical nevi, and 15 common nevi. Main Outcome Measures: Features referring to aspect, size, regularity, homogeneity, and infiltration of dermal papillae and to cellular size, regularity, and atypia were described by 2 observers on confocal images. Mean dermal papillary diameter, mean cell area, and shape irregularity were quantified by drawing papillae and cell contours on confocal images and measured with the use of a computer program. Results: Pigment network in melanomas consisted of large basal cells that circumscribed small to medium-sized dermal papillae with marked cellular atypia, sometimes infiltrating dermal papillae. On the other hand, common acquired nevi were characterized by lack of atypical cells and edged dermal papillae. Atypical nevi presented intermediate characteristics between clearly benign and malignant lesions. Conclusion: Cellular atypia was the most sensitive feature for melanoma diagnosis, whereas the presence of nucleated cells infiltrating dermal papillae was the most specific one.

In this paper we propose a system for automatic detection of shots in sport videos. Our work covers two main aspects: the first is robust shot detection in presence of fast object motion and camera operations. To this aim we propose a new algorithm, unique for both cuts and linear transitions detection, which only needs the tuning of two parameters. An extended comparison with four transition detection algorithms, representing the state of the art in literature, is reported. Examples with formula 1, basket, soccer and cycling videos are analyzed. The second aspect is an in depth discussion on the annotation of shots and transitions with the MPEG-7 standard.

Background/purpose: Since in early melanoma (MM) and especially in in situ MM differential structures, which are diagnostic for MM may be lacking, pigment distribution asymmetry represents an important diagnostic feature. Our aim was to automatically assess pigment distribution in images referring to MMs, atypical nevi (AN) and clearly benign nevi (BN), and to evaluate the diagnostic capability of numerical parameters describing a non homogeneous distribution of pigmentation. Methods: An image analysis program enabling the numerical assessment of pigment distribution in melanocytic lesions (ML), based on evaluation and comparison of red, green, blue (RGB) colour components inside image colour blocks, was employed on 459 videomicroscopic digital images, referring to 95 MMs, 76 AN and 288 BN. Results: Significant differences in pigment distribution parameters (mean RGB distance, variance and maximum distance) between the three ML populations were observed, permitting a good discrimination of MMs. On the test set comprising 230 lesion images, the area under the curve value of the receiver operating characteristic curve was 0.933. For a D score equal to 0, corresponding to the best diagnostic accuracy (86.6%), a sensitivity of 87.5% and a specificity of 85.7% were obtained. Conclusion: This original evaluation method for digital pigment distribution, based on mathematical description and comparison of colours in different image blocks, provides numerical parameters to be implemented in image analysis programs for computer-aided MM diagnosis.

Background/purpose: The assessment of colors is essential for melanoma (MM) diagnosis, both for pattern analysis on dermoscopic images, and when using semiquantitative methods. Our aim was to provide a simple, precise characterization and reproducible calibration of the color response for dermoscopic instruments. Methods: Three processes were used to correct the non-uniform illumination pattern of the instrument, to easily estimate the camera gamma settings and to describe the color space conversion matrices required to produce standard images, in any color space. A specific color space was also developed to optimize the representation of dermatoscopic colors. The calibration technique was tested both on synthetic reference surfaces and on real images by comparing the difference between the images colors obtained with two different equipments. Results: The differences between the images acquired by means of the two instruments, calculated on the reference patterns after calibration, were up to 10 times lower then before, while comparison of histograms referring to real images provided an improvement of about seven times on average. Conclusions: A complete workflow for dermatologic image calibration, which allows the user to continue using his own software and algorithms, but with a much higher informative content, is presented. The technique is simple and may improve cooperation between different research centers, in teleconsulting contexts or for result comparisons.

Computer vision and ubiquitous multimedia access nowadays make feasible the development of a mostly automated system for human-behavior analysis. In this context, our proposal is to analyze human behaviors by classifying the posture of the monitored person and, consequently, detecting corresponding events and alarm situations, like a fall. To this aim, our approach can be divided in two phases: for each frame, the projection histograms (Haritaoglu et al., 1998) of each person are computed and compared with the probabilistic projection maps stored for each posture during the training phase; then, the obtained posture is further validated exploiting the information extracted by a tracking module in order to take into account the reliability of the classification of the first phase. Moreover, the tracking algorithm is used to handle occlusions, making the system particularly robust even in indoors environments. Extensive experimental results demonstrate a promising average accuracy of more than 95% in correctly classifying human postures, even in the case of challenging conditions.

In this paper we describe general algorithms that are devised for MPEG-7 automatic annotation of Formula 1 videos, and in particular for camera-car shots detection. We employed a shot detection algorithm suitable for cuts and linear transitions detection, which is able to precisely detect both the transition's center and length. Statistical features based on MPEG motion compensation vectors arc then employed to provide motion characterization, using a subset of the motion types defined in MPEG-7, and shot type classification. Results on shot detection and classification are provided.

Metadata extraction is one of the first tasks to be performed for automatic Digital Library annotation, and in particular shot detection has been widely explored in literature. While a lot of methods have been proposed for the detection of abrupt cuts, only a small number of them has explicitly addressed the problem of gradual transitions. In this paper we propose an algorithm that exploits a precise model of linear transition. Experimental results on Formula 1 car races videos show the robustness of this method. These test videos are characterized by extreme situations such as fast camera and objects motion and very different kinds of shots. The algorithm is able to estimate the exact length of the transition and an error score is also given as a fitness measure to the linear model, to discriminate true transitions from false detections. The final shot segmentation is delivered as an MPEG7 compliant output.

This year, the joint team of UCF and the University of Modenahas participated in the following tasks: (1) shot boundarydetection, (2) low-level feature extraction, (3) high-levelfeature extraction, (4) topic search and (5) BBC rushes management.The shot boundary detection was contributed bythe Image Lab at the University of Modena. The other taskswere performed by the Computer Vision Team at UCF.

The assessment of asymmetry is essential for melanoma (MM) diagnosis, both when using a heuristic approach and when employing semiquantitative methods on dermoscopic images. The aim of our study was to develop and validate a software for assessment of asymmetry in melanocytic lesion images, based on evaluation of color symmetry, and to compare the automatic evaluation to the one performed by human observers. An image analysis program enabling the numerical assessment of asymmetry in melanocytic lesions, based on evaluation and comparison of RGB color components inside image color blocks, was employed on 459 videomicroscopic digital images, referring to 95 melanomas (MMs), 76 atypical nevi (AN) and 288 clearly benign nevi (BN). Clinical evaluation of asymmetry on dermoscopic images was performed on the same image set employing a 0–1 scoring system. Asymmetry judgement was expressed by the clinicians for 12.8% of BN, 44.7% of AN, and for 64.2% of MMs, whereas the computer identified 6.9% of BN, 27.6% of AN, and 87.4% of MMs as asymmetric. Sensitivity and specificity of clinical judgement were 64.2 and 80.5%, respectively, whereas for computer evaluation, a sensitivity of 87.5% and a specificity of 85.7% were obtained. Numerical parameters (mean RGB distance, variance and maximum distance) referring to MMs were significantly higher both with respect to BN and AN. This innovative method for automatic asymmetry evaluation, based on the mathematical description of color distribution in different image blocks, provides numerical parameters for employment in computer-aided melanoma diagnosis.

The aim of this study was to develop a computerized method for the identification and description of colour areas in melanocytic lesion images based on an approach mimicking the human perception of colours. A colour palette comprising six colour groups (black, dark brown, light brown, blue-grey, red and white) was created by selecting single colour components within melanocytic lesion images acquired using a digital videomicroscope, and was implemented in the image analysis program. For each colour region, the area, the distance from the lesion centroid, the spread, the colour area distribution in the internal and the external part of the lesion, and asymmetries were assessed on 604 melanocytic lesion images in our image database. Black, white and blue-grey colour areas were detected more frequently in melanomas compared with naevi. Moreover, significant differences in colour descriptors were observed for each colour group, showing that colour areas are more unevenly distributed in melanomas compared with naevi. Using a discriminant analysis approach, the extension of dark, white and blue-grey areas and some descriptors of the distribution of the colour areas were identified as the most relevant colour parameters for differentiating between benign and malignant lesions. In conclusion, our automatic procedure breaks down the image into the colour areas used in the clinical examination process, and also supplies a description of their extension and distribution, with parameters that correlate with the clinical concepts of regularity and homogeneity.