Publications by Costantino Grana

Background: Spitz nevus is a benign melanocytic lesion sometimes mistakenly diagnosed clinically as melanoma. Objective: Our aim was to evaluate in vivo reflectance-mode confocal scanning laser microscopy (CSLM) aspects of globular Spitz nevi and to correlate them with those of surface microscopy and histopathology. Methods: A total of 6 Spitz nevi, with globular aspects on epiluminescence observation, were imaged with CSLM and subsequently excised for histopathologic examination. Results: A close correlation among CSLM, epiluminescence, and histopathologic aspects was observed. Individual cells, observed in high-resolution confocal images, were similar in shape and dimension to the histopathologic ones. Lesion architecture was described on reconstructed CSLM images. Melanocytic nests corresponded to globular cellular aggregates at confocal microscopy and to globules at epiluminescence observation. Melanophages were clearly identified in the papillary dermis both by confocal microscopy and histopathology. Conclusion: In vivo CSLM enabled the identification of characteristic cytologic and architectural aspects of Spitz nevi, correlated with histopathology and epiluminescence microscopy observation.

We describe an integrated solution devised for inhouse video surveillance, to control the safety of people living in a domestic environment. The system is composed of robust moving object detection module, able to disregard shadows, a tracking module designed for large occlusion solution and of a posture detector. Shadows, large occlusions and deformable model of people are key features of inhouse surveillance. Moreover, the requirements of high speed reaction to dangerous situations and the need to implement a reliable and low cost televiewing system, led to the introduction of a new multimedia model of semantic transcoding, capable of supporting different user's requests and constraints of their devices (PDA, smart phones, ...). Our application context is the emerging area of domotics (from the Latin word domus that means "home" and informatics) and, in particular, indoor video surveillance of the house where people with some difficulties (elders and disabled people) can now live in a sufficient degree of autonomy, thanks to the strong interaction with the new technologies that can be distributed in the house with affordable costs and high reliability.

In this work, we describe a technique to calibrate images for skin analysis in dermatology. Using a common reference we correct non-uniform illumination effects, give an estimation of the gamma correction and produce a XYZ conversion matrix. The final result is then reverted to a non standard RGB color space, built from the instrument images. In this way different instruments behave uniformly allowing colorimetric characterization, while improving the results of common algorithms. The proposed techniques should be the initial support for a distributed framework where dermatological images can be consistently compared.

Spitz nevi may be often confused with malignant melanoma, because of its rapid growth and alarming clinical features. In vivo confocal reflectance microscopy (CRM) is a novel technique enabling the noninvasive imaging of the skin at a cellular level resolution. Twelve Spitz and 25 melanomas (MMs) were studied by means of CRM (Vivascope 1000, Lucid Inc., USA) and digital dermoscopy (Videocap 200, DS-Mediroup, Italy) for in vivo characterization of cytological and architectural features at CRM, and correlation with dermoscopy and histology. Although large cells with bright cytoplasm and dark eccentric nucleus, sometimes spreading upwards in a pagetoid fashion, were observed both in Spitz nevi and MMs, in the latter case they were more numerous and irregularly shaped. Dermoscopic globules corresponded to cell clusters at CRM and melanocytic nests at histopathology. Spitz nevi frequently presented a peripheral rim of medium sized peripheral clusters, constituted by compact aggregates of large polygonal cells, sometimes observable also on the whole lesion area. In MMs cell clusters were frequently constituted by sparse cells intercalated with thin fibrils giving a multi-lobate appearance or by large confluent aggregates of low reflecting polygonal or elongated cells, resulting in a cerebriform appearance. Although CRM appeared useful for distinction between melanocytic lesions, Spitz nevi presenting numerous atypical cells and dermal-epidermal architecture disarrangement can not be always distinguished from MMs, owing to the limited penetration of the near-infrared laser light, not enabling the evaluation of ‘cell maturation’ with increasing depth.

Typical processes of image representation comprehend initial region segmentation followed by a description of single regions’ feature and their relationships. Then a graph model can be exploited in order to integrate the knowledge of the specific regions (that are the attributed relational graph’s (ARG) nodes) and the regions’ relations (that are the ARG’s edges). In this work we use color features to guide region segmentation, geometric features to characterize regions one by one and topological features (and in particular inclusion) to describe regions’ relationships. Guided by the inclusion property we define the Topological Tree (TT) as an image representation model that exploiting the transitive property of inclusion, uses the adjacency and inclusion topological features. We propose an approach based on a recursive version of fuzzy c-means to construct the topological tree directly from the initial image, performing both segmentation and TT construction. The TT can be exploited in many applications of image analysis and image retrieval by similarity in those contexts where inclusion is a key feature: we propose an applicative case of analysis of dermatological images to support the melanoma diagnosis.In this paper describe details of the TT algorithm, including the management of not ideality and an approximate measure of tree similarity in order to retrieve skin lesion with a similar TT-based description.

In this work we present a framework for on-the-fly video transcoding that exploits computer vision-based techniques to adapt the Web access to the user requirements. Theproposed transcoding approach aims at coping with both user bandwidth and resources capabilities, and with user interests in the video's content. We propose an object-basedsemantic transcoding that, according to the user-dened classes of relevance, applies different transcoding techniques to the objects segmented in a scene. Object extraction is provided by on-the-fly video processing, without manual annotation. Multiple transcoding policies are reviewed and a performance evaluation metric based on the Weighted Mean Square Error (and corresponding PSNR), that takes into account the perceptual user requirements by means of classes of relevance, is dened. Results are analyzed by varying transcoding techniques, bandwidth requirements and video types (with indoor and outdoor scenes), showing that the use of semantics can dramatically improve the bandwidth to distortion ratio.

In contrast with common naevi, which generally show a homogeneous and regularly distributed pigmentation, brown to black pigment areas with irregular shape or asymmetric distribution are frequently observable in melanomas. Identification of dark areas inside a melanocytic lesion is of great importance for melanoma diagnosis, both during clinical examination and employing programs for automated image analysis. The aim of our study was to compare two different methods for the automated identification and description of dark areas in epiluminescence microscopy images of melanocytic lesions and to evaluate their diagnostic capability. 339 images of melanocytic lesions, referring to 113 melanomas and 226 melanocytic naevi, acquired by means of a polarizedlight videomicroscope (Videocap 200, DS-medica, Italy) with a 20 fold magnification were studied. Two different methods were employed for the identification of dark areas: the first permits the identification of ‘absolute’ dark areas, defined as areas which are darker than the skin. The second identifies the lesion area, the darkest with respect to the overall brightness of the lesion (‘relative’ dark areas). A set of parameters is extracted both for ‘absolute’ and ‘relative’ dark areas, in order to numerically describe the region properties, such as extension, balance, regularity and symmetry of its distribution. Significant differences in dark area distribution between melanomas and naevi were observed employing both methods, permitting a good discrimination of melanocytic lesions (diagnostic accuracy = 74.6% and 71.2% for absolute and relative dark areas, respectively). In conclusion, both methods for automated identification of dark areas are useful for melanoma diagnosis and can be implemented in programs for image analysis.

Monitoring and controlling the driver’s guidance by analyzing the rotation impressed to the steering-wheel can be a very important task in order to improve safety. This paper proposes a general-purpose method to track the steering wheel’s absolute angle by using a single camera vision system mounted inside the car. The absolute angle is computed by means of the accumulation of inter-frame relative rotations and the error propagation is prevented with an alignment process. The approach is based on the modeling of the motion of the steering wheel, as it appears perspectivelydistorted by the point of view of the un-calibrated camera. We modified the Lucas-Kanade method for an approximatively rotational motion model in order to provide the detection and tracking of significant features on the wheel. The experimental results are compared with ground-truthed data obtained with different types of sensors.

The paper presents an approach for a robust (semi-)automatic correction of radial lens distortion in images and videos. This method, based on the Hough transform, has the characteristics to be applicable also on videos from unknown cameras that, consequently, can not be a priori calibrated. We approximated the lens distortion by considering only the lower-order term of the radial distortion. Thus, the method relies on the assumption that pure radial distortion transforms straight lines into curves. The computation of the best value of the distortion parameter is performed in a multi-resolution way. The method precision depends on the scale of the multi-resolution and on the Hough space's resolution. Experiments are provided for both outdoor, uncalibrated camera and an indoor, calibrated one. The stability of the value found in different frames of the same video demonstrates the reliability of the proposed method.

The aim of this study was to provide mathematical descriptors for the border of pigmented skin lesion images and to assess their efficacy for distinction among different lesion groups. New descriptors such as lesion slope and lesion slope regularity are introduced and mathematically defined. A new algorithm based on the Catmull-Rom spline method and the computation of the gray-level gradient of points extracted by interpolation of normal direction on spline points was employed. The efficacy of these new descriptors was tested on a data set of 510 pigmented skin lesions, composed by 85 melanomas and 425 nevi, by employing statistical methods for discrimination between the two populations.