Gaetano Impoco

Experimental methodology for digital breast shape analysis and objective surgical outcome evaluation

Outcome evaluation in cosmetic and reconstructive surgery of the breast is commonly performed visually or employing bi-dimensional photography. The reconstructive process in the era of anatomical implants requires excellent survey capabilities that mainly rely on surgeon experience. In this paper we present a set of parameters to unambiguously estimate the shape of natural and reconstructed breast. A digital laser scanner was employed on seven female volunteers. A graphic depiction of curvature of the thoracic surface has been the most interesting result. Further work is required to provide clinical and instrumental validation to our technique.

An efficient Re-indexing algorithm for color-mapped images

The efficiency of lossless compression algorithms for fixed-palette images (indexed images) may change if a different indexing scheme is adopted. Many lossless compression algorithms adopt a differential-predictive approach. Hence, if the spatial distribution of the indexes over the image is smooth, greater compression ratios may be obtained. Because of this, finding an indexing scheme that realizes such a smooth distribution is a relevant issue. Obtaining an optimal re-indexing scheme is suspected to be a hard problem and only approximate solutions have been provided in literature. In this paper, we restate the re-indexing problem as a graph optimization problem: an optimal re-indexing corresponds to the heaviest Hamiltonian path in a weighted graph. It follows that any algorithm which finds a good approximate solution to this graph-theoretical problem also provides a good re-indexing. We propose a simple and easy-to-implement approximation algorithm to find such a path. The proposed technique compares favorably with most of the algorithms proposed in literature, both in terms of computational complexity and of compression ratio.

Video Enhancement and Dynamic Range Control of HDR Sequences for Automotive Applications

CMOS video cameras with high dynamic range (HDR) output are particularly suitable for driving assistance applications, where lighting conditions can strongly vary, going from direct sunlight to dark areas in tunnels. However, common visualization devices can only handle a low dynamic range, and thus a dynamic range reduction is needed. Many algorithms have been proposed in the literature to reduce the dynamic range of still pictures. Anyway, extending the available methods to video is not straightforward, due to the peculiar nature of video data. We propose an algorithm for both reducing the dynamic range of video sequences and enhancing its appearance, thus improving visual quality and reducing temporal artifacts. We also provide an optimized version of our algorithm for a viable hardware implementation on an FPGA. The feasibility of this implementation is demonstrated by means of a case study.

Using a Recursive Rational Filter to Enhance Color Images

Portable image acquisition devices often operate in challenging outdoor environments. The quality of the acquired scenes is often low due to the low dynamics of current sensors. Moreover, these sensors are typically equipped with low-cost hardware. Hence, the image-enhancement algorithms are bounded to work in real time using limited resources and possibly require low power. We introduce a novel method to enhance the digital images acquired in critical lighting conditions, producing high-quality images for most applications. Our algorithm separates the image into illumination and reflectance, as in the ldquoRetinexrdquo theory. These two channels are separately processed since they give different contributions to the image. We propose a simple and fast operator to estimate the illumination component employing a spatially recursive rational filter. We show some results of an extensive experimental phase to show that to separately process the illumination and reflectance channels is advantageous since the image features are better exploited. A number of measures are computed to validate our choices.

Objective outcome evaluation of breast surgery

A new method is proposed to unambiguously define a geometric partitioning of 3D models of female thorax. A breast partitioning scheme is derived from simple geometric primitives and well-defined anatomical points. Relevant measurements can be extrapolated from breast partition. Our method has been tested on a number of breast 3D models acquired by means of a commercial scanner on real clinical cases.

A colour reindexing algorithm for lossless compression of digital images

The efficiency of lossless compression algorithms for fixed palette images (also called indexed images) changes if a different indexing scheme is adopted. Indeed, these algorithms adopt a differential-predictive approach of some sort: if the spatial distribution of the indexes over the image is smooth, greater compression ratios may be obtained. It hence becomes relevant to find an indexing scheme that realizes such a smooth distribution. This seems to be a hard problem, and only approximate answers can be provided if a realistic run-time has to be achieved. In this paper, we propose a new indexing scheme, based on an approximate algorithm that maximizes the cost of a Hamiltonian path in a weighted graph. The proposed technique compares favourably with the algorithm proposed by W. Zeng et al. (2000). The computational complexity of the two algorithms is compared and experimental tests that show that relative compression rates are reported.

Structural Simulation of a Bone-Prosthesis System of the Knee Joint

In surgical knee replacement, the damaged knee joint is replaced with artificial prostheses. An accurate clinical evaluation must be carried out before applying knee prosthe-ses to ensure optimal outcome from surgical operations and to reduce the probability of having long-term problems. Useful information can be inferred from estimates of the stress acting onto the bone-prosthesis system of the knee joint. This information can be exploited to tailor the prosthesis to the patients anatomy. We present a compound system for pre-operative surgical planning based on structural simulation of the bone-prosthesis system, exploiting patient-specific data.

Adaptive reduction of the dynamics of HDR video sequences

A new generation of acquisition devices with high dynamics is rapidly overcoming the limitations of current hardware. The dynamic range of visualisation devices is lower by some orders of magnitude with respect to acquisition hardware. Dedicated algorithms are needed to fill the gap between the high dynamics of acquired scenes and the low dynamic range of visualisation devices. We propose a novel approach to reduce adaptively the dynamics of video sequences to fit the display range. Our algorithm takes into account time relationships between neighbouring frames to avoid annoying artifacts.

Level Set Segmentation of Knee Bones Using Normal Profile Models

We address the problem of segmenting bone structures from CT scans of the knee joint, in the level set framework. Our method is based on intensity profiles along the normals to the evolving contour. The evolution is guided by the similarity of image intensity profiles to profile models. The evolution stops when the intensity profiles closely match the model. The profile models are built using a manually labelled training sample.

An Interactive Level Set Approach to Semi-automatic Detection of Features in Food Micrographs

Microscopy is often employed in food research to inspect the microstructural features of food samples. Accurate detection of microscopic features is required for reliable quantitative analysis. We propose a user-assisted approach that can be easily integrated into a graphical interface. The proposed algorithm is based on a fast approximation of the common region-based level set equation, providing interactive computations. Experiments have been run on cheese micrographs acquired with electron and confocal microscopes.