Search

Objectives To identify barriers to the use of nailfold capillaroscopy as a diagnostic tool for patients presenting with Raynaud's phenomenon in UK rheumatology centres and to obtain rheumatologists' views on a proposed internet-based standardized system for clinical reporting of nailfold capillaroscopy images. Methods An online survey was developed using expert opinion from clinicians, scientists and health service researchers. The survey was piloted and sent to UK-based rheumatologists using established electronic mailing lists between October 2020 and March 2021. Survey data were analysed using descriptive statistics. Results A total of 104 rheumatologists representing rheumatology centres across the UK responded to the survey. Wide variations in terms of workloads and practices were described. Thirty-four (33%) respondents reported using nailfold capillaroscopy only at their own centre, 33 (32%) referred to other centres, 9 (9%) did both and 28 (27%) did not use capillaroscopy at all. Of the 43 respondents using capillaroscopy on site, 25 (58%) used either a dermatoscope or universal serial bus microscope and 9 (21%) used videocapillaroscopy. Among the 61 respondents not undertaking capillaroscopy on site, barriers included lack of equipment (85%), lack of experience in acquiring images (69%) and lack of expertise in interpreting images (67%). Sixty-six respondents (63%) expressed interest in an internet-based, standardized automated system for reporting images. Conclusion Most UK rheumatologists currently do not perform nailfold capillaroscopy on site. An internet-based nailfold capillaroscopy system for use with low-cost microscopes as well as with videocapillaroscopy could help increase uptake of capillaroscopy and thereby facilitate early diagnosis of SSc across the UK. [ABSTRACT FROM AUTHOR]

We describe a method for automatically building statistical shape models from a training set of example boundaries/surfaces. These models show considerable promise as a basis for segmenting and interpreting images. One of the drawbacks of the approach is, however, the need to establish a set of dense correspondences between all members of a set of training shapes. Often this is achieved by locating a set of 'landmarks' manually on each training image, which is time consuming and subjective in two dimensions and almost impossible in three dimensions. We describe how shape models can be built automatically by posing the correspondence problem as one of finding the parameterization for each shape in the training set. We select the set of parameterizations that build the 'best' model. We define 'best' as that which minimizes the description length of the training set, arguing that this leads to models with good compactness, specificity and generalization ability. We show how a set of shape parameterizations can be represented and manipulated in order to build a minimum description length model. Results are given for several different training sets of two-dimensional boundaries, showing that the proposed method constructs better models than other approaches including manual landmarking--the current gold standard. We also show that the method can be extended straightforwardly to three dimensions. Index Terms--Active shape models, automatic landmarking, correspondence problem, minimum description length (MDL), point distribution models, statistical shape modeling.

The process of aging causes significant alterations in the facial appearance of individuals. When compared with other sources of variation in face images, appearance variation due to aging displays some unique characteristics. For example, aging variation is specific to a given individual; it occurs slowly and is affected significantly by other factors, such as health, gender, and lifestyle. Changes in facial appearance due to aging can even affect discriminatory facial features, resulting in deterioration of the ability of humans and machines to identify aged individuals. In this paper, we describe how the effects of aging on facial appearance can be explained using learned age transformations and present experimental results to show that reasonably accurate estimates of age can be made for unseen images. We also show that we can improve our results by taking into account the fact that different individuals age in different ways and by considering the effect of lifestyle. Our proposed framework can be used for simulating aging effects on new face images in order to predict how an individual might look like in the future or how he/she used to look in the past. The methodology presented has also been used for designing a face recognition system, robust to aging variation. In this context, the perceived age of the subjects in the training and test images is normalized before the training and classification procedure so that aging variation is eliminated. Experimental results demonstrate that, when age normalization is used, the performance of our face recognition system can be improved. Index Terms--Aging variation, statistical face models, face recognition.

Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression, and lighting. We describe a compact parametrized model of facial appearance which takes into account all these sources of variability. The model represents both shape and gray-level appearance, and is created by performing a statistical analysis over a training set of face images. A robust multiresolution search algorithm is used to fit the model to faces in new images. This allows the main facial features to be located, and a set of shape, and gray-level appearance parameters to be recovered. A good approximation to a given face can be reconstructed using less than 100 of these parameters. This representation can be used for tasks such as image coding, person identification, 3D pose recovery, gender recognition, and expression recognition. Experimental results are presented for a database of 690 face images obtained under widely varying conditions of 3D pose, lighting, and facial expression. The system performs well on all the tasks listed above. Index Terms - Face recognition, expression recognition, pose recovery, coding-reconstruction, facial feature location, deformable templates.

A framework for automatic landmark indentification is presented based on an algorithm for corresponding the boundaries of two shapes. The auto-landmarking framework employs a binary tree of corresponded pairs of shapes to generate landmarks automatically on each of a set of example shapes. The landmarks are used to train statistical shape models known as Point Distribution Models. The correspondence algorithm locates a matching pair of sparse polygonal approximations, one for each of a pair of boundaries by minimizing a cost function, using a greedy algorithm. The cost function expresses the dissimilarity in both the shape and representation error (with respect to the defining boundary) of the sparse polygons. Results are presented for three classes of shape which exhibit various types of nonrigid deformation. Index Terms--Correspondence, critical points, polygonal approximation, automatic landmarks, flexible templates, point distribution models.