PubMed Health⌕ Search

Biomedical subjects

Anil K Jain

Publications and source records attributed to Anil K Jain.

At least 19 recordsLinked to original sources
PubMed2006

Osteochondroma of C7 vertebra presenting as compressive myelopathy in a patient with nonhereditary (nonfamilial/sporadic) multiple exostoses.

INTRODUCTION: Osteochondromas are most commonly found in the appendicular skeleton. They occur less frequently in the spine and compression of the spinal cord is very rare. To the best of our knowledge, this is the first report of an osteochondroma arising from C7 vertebra presenting with compressive myelopathy in a patient with nonhereditary multiple exostoses. Our purpose is to report this rare presentation and its successful management, and to highlight the clinico-radiological features of this treatable condition. MATERIALS AND METHODS: A 20-year-old male with nonhereditary exostoses presented with gradual onset weakness in bilateral lower limbs, which had rapidly progressed to complete paraplegia over 1 month. The tumor was effectively treated by surgical excision along with spinal decompression. The diagnosis was confirmed by histopathological evidence complemented by clinico-radiological studies. RESULTS: There has been a complete functional recovery without any evidence of recurrence at last follow-up at 2 years. CONCLUSION: Compressive myelopathy due to an osteochondroma arising from C7 vertebra in a case with nonhereditary multiple exostoses is being reported for the first time. Both CT and MRI demonstrated the origin, size, extent and relationship of the tumor to the vertebral and neural elements. Complete recovery of functions after surgical decompression was achieved in this case. An osteochondroma of spine must always be considered in all patients with multiple exostoses who have spine pain or develop neural deficit.

Adult↗
PubMed2006

Extraskeletal paraarticular osteochondroma of the knee--a case report and tumor overview.

Extraskeletal paraarticular osteochondromas are rather unusual osteocartilaginous lesions that arise in the soft tissues adjacent to the joint with no bony or joint continuity. This diagnosis should be considered with the demonstration of a well-circumscribed extraskeletal mineralized mass without any direct continuity with adjacent bone or joint. However, as with other lesions, clinicoradiographic features with histological correlation clinch the diagnosis. Differentiation from other lesions, particularly synovial osteochondromatosis and chondrosarcoma is essential to avoid unnecessary aggressive surgical procedures as marginal excision is adequate for these lesions. We present here such an infrapatellar lesion and discuss criteria helpful in distinguishing these benign lesions from other morphological similar lesions.

Adult↗
PubMed2006

Concomitant multiple closed contiguous physeal injuries in a limb with an undescribed 'distractional-separation' type with vascular compromise: a report of two cases.

INTRODUCTION: Though physeal injuries are common in children, concomitant multiple closed contiguous physeal injuries in a limb along with vascular compromise are rare. An associated distractional-separation type of physeal injury is being documented for the first time. We present here two such cases. MATERIALS AND METHODS: Two children, aged 6 months and 3 years, respectively, suffered a roadside high velocity trauma and thus form the part of this case report. RESULTS: Because of the delay in seeking treatment and, or, the nature of injuries, it was associated with a tragic complication--an amputation in both cases. CONCLUSION: Although, the limb in our cases could not be salvaged, these reports describe these unusual injury patterns for the first time and re-emphasize the awareness of urgent recognition of the associated vascular insult.

Accidents, Traffic↗
PubMed2006

Fingerprint warping using ridge curve correspondences.

The performance of a fingerprint matching system is affected by the nonlinear deformation introduced in the fingerprint impression during image acquisition. This nonlinear deformation causes fingerprint features such as minutiae points and ridge curves to be distorted in a complex manner. A technique is presented to estimate the nonlinear distortion in fingerprint pairs based on ridge curve correspondences. The nonlinear distortion, represented using the thin-plate spline (TPS) function, aids in the estimation of an "average" deformation model for a specific finger when several impressions of that finger are available. The estimated average deformation is then utilized to distort the template fingerprint prior to matching it with an input fingerprint. The proposed deformation model based on ridge curves leads to a better alignment of two fingerprint images compared to a deformation model based on minutiae patterns. An index of deformation is proposed for selecting the "optimal" deformation model arising from multiple impressions associated with a finger. Results based on experimental data consisting of 1,600 fingerprints corresponding to 50 different fingers collected over a period of two weeks show that incorporating the proposed deformation model results in an improvement in the matching performance.

Algorithms↗
PubMed2006

Matching 2.5D face scans to 3D models.

The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system that utilizes three-dimensional shape information to make the system more robust to arbitrary pose and lighting. For each subject, a 3D face model is constructed by integrating several 2.5D face scans which are captured from different views. 2.5D is a simplified 3D (x, y, z) surface representation that contains at most one depth value (z direction) for every point in the (x, y) plane. Two different modalities provided by the facial scan, namely, shape and texture, are utilized and integrated for face matching. The recognition engine consists of two components, surface matching and appearance-based matching. The surface matching component is based on a modified Iterative Closest Point (ICP) algorithm. The candidate list from the gallery used for appearance matching is dynamically generated based on the output of the surface matching component, which reduces the complexity of the appearance-based matching stage. Three-dimensional models in the gallery are used to synthesize new appearance samples with pose and illumination variations and the synthesized face images are used in discriminant subspace analysis. The weighted sum rule is applied to combine the scores given by the two matching components. Experimental results are given for matching a database of 200 3D face models with 598 2.5D independent test scans acquired under different pose and some lighting and expression changes. These results show the feasibility of the proposed matching scheme.

Algorithms↗
PubMed2006

Performance evaluation of fingerprint verification systems.

This paper is concerned with the performance evaluation of fingerprint verification systems. After an initial classification of biometric testing initiatives, we explore both the theoretical and practical issues related to performance evaluation by presenting the outcome of the recent Fingerprint Verification Competition (FVC2004). FVC2004 was organized by the authors of this work for the purpose of assessing the state-of-the-art in this challenging pattern recognition application and making available a new common benchmark for an unambiguous comparison of fingerprint-based biometric systems. FVC2004 is an independent, strongly supervised evaluation performed at the evaluators' site on evaluators' hardware. This allowed the test to be completely controlled and the computation times of different algorithms to be fairly compared. The experience and feedback received from previous, similar competitions (FVC2000 and FVC2002) allowed us to improve the organization and methodology of FVC2004 and to capture the attention of a significantly higher number of academic and commercial organizations (67 algorithms were submitted for FVC2004). A new, "Light" competition category was included to estimate the loss of matching performance caused by imposing computational constraints. This paper discusses data collection and testing protocols, and includes a detailed analysis of the results. We introduce a simple but effective method for comparing algorithms at the score level, allowing us to isolate difficult cases (images) and to study error correlations and algorithm "fusion." The huge amount of information obtained, including a structured classification of the submitted algorithms on the basis of their features, makes it possible to better understand how current fingerprint recognition systems work and to delineate useful research directions for the future.

Algorithms↗
PubMed2006

Incremental nonlinear dimensionality reduction by manifold learning.

Understanding the structure of multidimensional patterns, especially in unsupervised cases, is of fundamental importance in data mining, pattern recognition, and machine learning. Several algorithms have been proposed to analyze the structure of high-dimensional data based on the notion of manifold learning. These algorithms have been used to extract the intrinsic characteristics of different types of high-dimensional data by performing nonlinear dimensionality reduction. Most of these algorithms operate in a "batch" mode and cannot be efficiently applied when data are collected sequentially. In this paper, we describe an incremental version of ISOMAP, one of the key manifold learning algorithms. Our experiments on synthetic data as well as real world images demonstrate that our modified algorithm can maintain an accurate low-dimensional representation of the data in an efficient manner.

Algorithms↗
PubMed2005

Neglected traumatic hip dislocation in children.

Traumatic dislocation of the hip in children is a rare injury. We report the outcome of open reduction of neglected traumatic posterior hip dislocation in 18 children. All patients had posterior dislocation and no associated fracture. They presented to the hospital because of persisting pain, deformity, and limp that were present for a mean period of 16 weeks after injury (range, 6-52 weeks). Open reduction was done in all patients because none of the hips could be reduced by skeletal traction in abduction. All of the hips had varying degrees of avascular necrosis (osteonecrosis), with preservation of joint space as seen on radiographs. At short term followup, seventeen children had an excellent functional outcome. We suggest that open reduction is a satisfactory treatment for neglected hip dislocation in children because an anatomically placed femoral head maintains the stimulus for growth of the pelvis and the femur. It prevents deformity and maintains limb length.

Bone Wires↗
PubMed2005

Infected nonunion of the long bones.

The problems in infected nonunion include multiple sinuses, osteomyelitis, bone and soft tissue loss, osteopenia, adjacent joint stiffness, complex deformities, limb-length inequalities, and multidrug-resistant polybacterial infection. Bone gap and active infection are the crucial factors relating to treatment and prognosis. Gaps larger than 4 cm likely cannot be effectively bridged by corticocancellous bone grafting. If the limb has intact distal circulation and sensation, limb salvage and reconstruction generally is preferable to amputation. The fracture generally unites if adequate debridement of the nonunion site is done with fracture stabilization and bone grafting. We reviewed 42 consecutive patients with infected nonunion of the long bones. These patients have been categorized into two groups. Type A is infected nonunion of long bones with nondraining (quiescent) infection, with or without implant in situ; Type B is infected nonunion of long bones with draining (active) infection. Both are classified further into two subtypes: 1) nonunion with a bone gap smaller than 4 cm or 2) nonunion with a bone gap larger than 4 cm. Single-stage debridement and bone grafting with fracture stabilization are the methods of choice for Type A1 infected nonunions. Adequate debridement, fracture stabilization, and second-stage bone grafting gives desirable results in Type B1 infected nonunions. Distraction histiogenesis is the preferred procedure for Type A2 and B2. The autogenous nonvascularized fibular graft, posterolateral bone grafting for the tibia, and centralization of the ulna over distal radial remnant (single bone forearm) may be good treatment options in selected cases.

Adolescent↗
PubMed2005

Editorial comment.

Explore the source record for details and available documents.

Developing Countries↗
PubMed2005

A wrapper-based approach to image segmentation and classification.

The traditional processing flow of segmentation followed by classification in computer vision assumes that the segmentation is able to successfully extract the object of interest from the background image. It is extremely difficult to obtain a reliable segmentation without any prior knowledge about the object that is being extracted from the scene. This is further complicated by the lack of any clearly defined metrics for evaluating the quality of segmentation or for comparing segmentation algorithms. We propose a method of segmentation that addresses both of these issues, by using the object classification subsystem as an integral part of the segmentation. This will provide contextual information regarding the objects to be segmented, as well as allow us to use the probability of correct classification as a metric to determine the quality of the segmentation. We view traditional segmentation as a filter operating on the image that is independent of the classifier, much like the filter methods for feature selection. We propose a new paradigm for segmentation and classification that follows the wrapper methods of feature selection. Our method wraps the segmentation and classification together, and uses the classification accuracy as the metric to determine the best segmentation. By using shape as the classification feature, we are able to develop a segmentation algorithm that relaxes the requirement that the object of interest to be segmented must be homogeneous in some low-level image parameter, such as texture, color, or grayscale. This represents an improvement over other segmentation methods that have used classification information only to modify the segmenter parameters, since these algorithms still require an underlying homogeneity in some parameter space. Rather than considering our method as, yet, another segmentation algorithm, we propose that our wrapper method can be considered as an image segmentation framework, within which existing image segmentation algorithms may be executed. We show the performance of our proposed wrapper-based segmenter on real-world and complex images of automotive vehicle occupants for the purpose of recognizing infants on the passenger seat and disabling the vehicle airbag. This is an interesting application for testing the robustness of our approach, due to the complexity of the images, and, consequently, we believe the algorithm will be suitable for many other real-world applications.

Algorithms↗
PubMed2005

Combining multiple clusterings using evidence accumulation.

We explore the idea of evidence accumulation (EAC) for combining the results of multiple clusterings. First, a clustering ensemble--a set of object partitions, is produced. Given a data set (n objects or patterns in d dimensions), different ways of producing data partitions are: 1) applying different clustering algorithms and 2) applying the same clustering algorithm with different values of parameters or initializations. Further, combinations of different data representations (feature spaces) and clustering algorithms can also provide a multitude of significantly different data partitionings. We propose a simple framework for extracting a consistent clustering, given the various partitions in a clustering ensemble. According to the EAC concept, each partition is viewed as an independent evidence of data organization, individual data partitions being combined, based on a voting mechanism, to generate a new n x n, similarity matrix between the n patterns. The final data partition of the n patterns is obtained by applying a hierarchical agglomerative clustering algorithm on this matrix. We have developed a theoretical framework for the analysis of the proposed clustering combination strategy and its evaluation, based on the concept of mutual information between data partitions. Stability of the results is evaluated using bootstrapping techniques. A detailed discussion of an evidence accumulation-based clustering algorithm, using a split and merge strategy based on the K-means clustering algorithm, is presented. Experimental results of the proposed method on several synthetic and real data sets are compared with other combination strategies, and with individual clustering results produced by well-known clustering algorithms.

Algorithms↗
PubMed2005

Dental biometrics: alignment and matching of dental radiographs.

Dental biometrics utilizes dental radiographs for human identification. The dental radiographs provide information about teeth, including tooth contours, elative positions of neighboring teeth, and shapes of the dental work (e.g., crowns, fillings, and bridges). The proposed system has two main stages: feature extraction and matching. The feature extraction stage uses anisotropic diffusion to enhance the images and a Mixture of Gaussians model to segment the dental work. The matching stage has three sequential steps: tooth-level matching, computation of image distances, and subject identification. In the tooth-level matching step, tooth contours are matched using a shape registration method, and the dental work is matched on overlapping areas. The distance between the tooth contours and the distance between the dental work are then combined using posterior probabilities. In the second step, the tooth correspondences between the given query (postmortem) radiograph and the database (antemortem) radiograph are established. A distance based on the corresponding teeth is then used to measure the similarity between the two radiographs. Finally, all the distances between the given postmortem radiographs and the antemortem radiographs that provide candidate identities are combined to establish the identity of the subject associated with the postmortem radiographs.

Algorithms↗
PubMed2005

Clustering ensembles: models of consensus and weak partitions.

Clustering ensembles have emerged as a powerful method for improving both the robustness as well as the stability of unsupervised classification solutions. However, finding a consensus clustering from multiple partitions is a difficult problem that can be approached from graph-based, combinatorial, or statistical perspectives. This study extends previous research on clustering ensembles in several respects. First, we introduce a unified representation for multiple clusterings and formulate the corresponding categorical clustering problem. Second, we propose a probabilistic model of consensus using a finite mixture of multinomial distributions in a space of clusterings. A combined partition is found as a solution to the corresponding maximum-likelihood problem using the EM algorithm. Third, we define a new consensus function that is related to the classical intraclass variance criterion using the generalized mutual information definition. Finally, we demonstrate the efficacy of combining partitions generated by weak clustering algorithms that use data projections and random data splits. A simple explanatory model is offered for the behavior of combinations of such weak clustering components. Combination accuracy is analyzed as a function of several parameters that control the power and resolution of component partitions as well as the number of partitions. We also analyze clustering ensembles with incomplete information and the effect of missing cluster labels on the quality of overall consensus. Experimental results demonstrate the effectiveness of the proposed methods on several real-world data sets.

Algorithms↗
PubMed2004

Online handwritten script recognition.

Automatic identification of handwritten script facilitates many important applications such as automatic transcription of multilingual documents and search for documents on the Web containing a particular script. The increase in usage of handheld devices which accept handwritten input has created a growing demand for algorithms that can efficiently analyze and retrieve handwritten data. This paper proposes a method to classify words and lines in an online handwritten document into one of the six major scripts: Arabic, Cyrillic, Devnagari, Han, Hebrew, or Roman. The classification is based on 11 different spatial and temporal features extracted from the strokes of the words. The proposed system attains an overall classification accuracy of 87.1 percent at the word level with 5-fold cross validation on a data set containing 13,379 words. The classification accuracy improves to 95 percent as the number of words in the test sample is increased to five, and to 95.5 percent for complete text lines consisting of an average of seven words.

Algorithms↗
PubMed2004

Simultaneous feature selection and clustering using mixture models.

Clustering is a common unsupervised learning technique used to discover group structure in a set of data. While there exist many algorithms for clustering, the important issue of feature selection, that is, what attributes of the data should be used by the clustering algorithms, is rarely touched upon. Feature selection for clustering is difficult because, unlike in supervised learning, there are no class labels for the data and, thus, no obvious criteria to guide the search. Another important problem in clustering is the determination of the number of clusters, which clearly impacts and is influenced by the feature selection issue. In this paper, we propose the concept of feature saliency and introduce an expectation-maximization (EM) algorithm to estimate it, in the context of mixture-based clustering. Due to the introduction of a minimum message length model selection criterion, the saliency of irrelevant features is driven toward zero, which corresponds to performing feature selection. The criterion and algorithm are then extended to simultaneously estimate the feature saliencies and the number of clusters.

Algorithms↗
PubMed2002

Treatment of tuberculosis of the spine with neurologic complications.

Neurologic complications are the most dreaded complication of spinal tuberculosis. The patients who have paraplegia develop in the active stage of tuberculosis of the spine require active treatment for spinal tuberculosis and have a better prognosis than the patients who have paraplegia develop many years after the initial disease has healed. Neurologic dysfunctions in association with active tuberculosis of the spine can be prevented by early diagnosis and prompt treatment. Prompt treatment can reverse paralysis and minimize the potential disability resulting from Pott's paraplegia. When needed, a combination of conservative therapy and surgical decompression yields successful results in most patients with tuberculosis of the spine who have neurologic complications. The vertebral body primarily is affected in tuberculosis; therefore, decompression has to be anterior. Laminectomy is advocated in patients with posterior complex disease and spinal tumor syndrome. Late onset paraplegia is best avoided by prevention of the development of severe kyphosis. Patients with tuberculosis of the spine who are likely to have severe kyphosis develop (< 60 degrees) on completion of treatment should have surgery in the active stage of disease to improve kyphus.

Algorithms↗