Biomedical subjects

Hany Farid

Publications and source records attributed to Hany Farid.

8 recordsLinked to original sources

PubMed2004

A digital technique for art authentication.

We describe a computational technique for authenticating works of art, specifically paintings and drawings, from high-resolution digital scans of the original works. This approach builds a statistical model of an artist from the scans of a set of authenticated works against which new works then are compared. The statistical model consists of first- and higher-order wavelet statistics. We show preliminary results from our analysis of 13 drawings that at various times have been attributed to Pieter Bruegel the Elder; these results confirm expert authentications. We also apply these techniques to the problem of determining the number of artists that may have contributed to a painting attributed to Pietro Perugino and again achieve an analysis agreeing with expert opinion.

Journal Article↗

PubMed2004

Recognizing and segmenting objects in clutter.

When viewing a cluttered scene, observers may not be able to segment whole objects prior to recognition. Instead, they may segment and recognize these objects in a piecemeal way. Here we test whether observers can use the appearance of one object part to predict the location and appearance of other object parts. During several training sessions, observers studied an object against a blank background. They then viewed this object against a background of clutter that camouflaged some parts of the object while leaving other parts salient. The observer's task was to find the camouflaged part. We varied the symmetry of the salient part with the expectation that as this symmetry decreased, the information about the camouflaged part's location and appearance would increase and this would facilitate search. Our results suggest that observers can use the salient part to predict the location, but not the appearance, of the camouflaged part.

Discrimination, Psychological↗

PubMed2004

Search for a category target in clutter.

An airport security worker searching a suitcase for a weapon is engaging in an especially difficult search task: the target is not well-specified, it is not salient, and it is not predicted by its context. Under these conditions, search may proceed item-by-item. In the experiment reported here we tested whether the items for this form of search are whole familiar objects. Our displays were composed of color photographs of ordinary objects, that were either uniform in color and texture (simple), or had two or more parts with different colors or textures (compound). The observer's task was to detect the presence of a target belonging to a broad category (food). We found that when the objects were presented in a sparse array, search times to find the target were similar for displays composed of simple and compound objects. But when the same objects were presented as dense clutter, search functions were steeper for displays composed of compound objects. We attribute this difference to the difficulty of segmenting compound objects in clutter: compared with simple objects, compound objects are less likely to be organized into a single object by bottom--up grouping processes. Our results indicate that while search rates in a sparse display may be determined by the number of objects, search rates in clutter are also affected by the number of object parts.

Adult↗

PubMed2004

Differentiation of discrete multidimensional signals.

We describe the design of finite-size linear-phase separable kernels for differentiation of discrete multidimensional signals. The problem is formulated as an optimization of the rotation-invariance of the gradient operator, which results in a simultaneous constraint on a set of one-dimensional low-pass prefilter and differentiator filters up to the desired order. We also develop extensions of this formulation to both higher dimensions and higher order directional derivatives. We develop a numerical procedure for optimizing the constraint, and demonstrate its use in constructing a set of example filters. The resulting filters are significantly more accurate than those commonly used in the image and multidimensional signal processing literature.

Algorithms↗

PubMed2003

Probabilistic disease classification of expression-dependent proteomic data from mass spectrometry of human serum.

We have developed an algorithm called Q5 for probabilistic classification of healthy versus disease whole serum samples using mass spectrometry. The algorithm employs principal components analysis (PCA) followed by linear discriminant analysis (LDA) on whole spectrum surface-enhanced laser desorption/ionization time of flight (SELDI-TOF) mass spectrometry (MS) data and is demonstrated on four real datasets from complete, complex SELDI spectra of human blood serum. Q5 is a closed-form, exact solution to the problem of classification of complete mass spectra of a complex protein mixture. Q5 employs a probabilistic classification algorithm built upon a dimension-reduced linear discriminant analysis. Our solution is computationally efficient; it is noniterative and computes the optimal linear discriminant using closed-form equations. The optimal discriminant is computed and verified for datasets of complete, complex SELDI spectra of human blood serum. Replicate experiments of different training/testing splits of each dataset are employed to verify robustness of the algorithm. The probabilistic classification method achieves excellent performance. We achieve sensitivity, specificity, and positive predictive values above 97% on three ovarian cancer datasets and one prostate cancer dataset. The Q5 method outperforms previous full-spectrum complex sample spectral classification techniques and can provide clues as to the molecular identities of differentially expressed proteins and peptides.

Algorithms↗

PubMed2003

Elastic registration in the presence of intensity variations.

We have developed a general-purpose registration algorithm for medical images and volumes. This method models the transformation between images as locally affine but globally smooth. The model also explicitly accounts for local and global variations in image intensities. This approach is built upon a differential multiscale framework, allowing us to capture both large- and small-scale transformations. We show that this approach is highly effective across a broad range of synthetic and clinical medical images.

Algorithms↗

PubMed2003

A noncontacting 3-D digitizer for use in image-guided neurosurgery.

Current neuronavigational systems face two primary challenges: (1) automatic and robust registration between preoperative images and the operating room space, and (2) compensation for brain deformations that compromise the accuracy of the initial registration. To contend with these difficulties, we firstly estimate the three-dimensional (3-D) structure of the cortical surface using a noncontacting 3-D digitizer. This 3-D structure is then used to establish the initial registration, and to update the preoperative MR volume as the brain deforms. We show that this approach improves the accuracy of registration in a phantom study, and demonstrate the ability to capture cortical motion in six clinical cases.

Cerebral Cortex↗

PubMed2002

Temporal synchrony in perceptual grouping: a critique.

It has been hypothesized that the human visual system can use temporal synchrony for the perceptual grouping of image regions into unified objects, as proposed in some neural models. It is argued here, however, that previous psychophysical evidence for this hypothesis is due to stimulus artifacts, and that earlier studies do not, therefore, support the claims of synchrony-sensitive grouping mechanisms or processes.

Journal Article↗