Unsupervised cell nucleus segmentation with active contours

The task of segmenting cell nuclei from cytoplasm in conventional Papanicolaou (Pap) stained cervical cell images is a classical image analysis problem which may prove to be crucial to the development of successful systems which automate the analysis of Pap smears for detection of cancer of the cervix. Although simple thresholding techniques will extract the nucleus in some cases, accurate unsupervised segmentation of very large image databases is elusive. Conventional active contour models as introduced by Kass, Witkin and Terzopoulos (1988) offer a number of advantages in this application, but suffer from the well-known drawbacks of initialisation and minimisation. Here we show that a Viterbi search-based dual active contour algorithm is able to overcome many of these problems and achieve over 99% accurate segmentation on a database of 20 130 Pap stained cell images. (C) 1998 Elsevier Science B.V. All rights reserved.

Predicting energy requirements in the clinical setting: Are current methods evidence based?

Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

New Specific Equation to Estimate Resting Energy Expenditure in Severely Obese Patients

Calculating the estimated resting energy expenditure (REE) in severely obese patients is useful, but there is controversy concerning the effectiveness of available prediction equations (PE) using body weight (BW). We evaluated the efficacy of REE equations against indirect calorimetry (IC) in severely obese subjects and aimed to develop a new equation based on body composition compartments. One hundred and twenty severely obese patients had their REE measured (MREE) by IC and compared to the most commonly used PE (Harris-Benedict (HB), Ireton-Jones, Owen, and Mifflin St. Jeor). In a random sample (n = 60), a new REE equation based on fat-free mass (FFM) was developed and validated. All PE studied failed to estimate REE in severe obesity (low concordance correlation coefficient (CCC) and limits of agreement of nearly 50% of the sample +/- 10% of MREE). The HB equation using actual BW exhibited good results for all samples when compared to IC (2,117 +/- 518 kcal/day by HB vs. 2,139 +/- 423 kcal/day by MREE, P > 0.01); these results were blunted when patients were separated by gender (2,771 vs. 2,586 kcal/day, P < 0.001 in males and 1,825 vs. 1,939 kcal/day, P < 0.001 in females). A new resting energy expenditure equation prediction was developed using FFM, Horie-Waitzberg, & Gonzalez, expressed as 560.43 + (5.39 x BW) + (14.14 x FFM). The new resting energy expenditure equation prediction, which uses FFM and BW, demonstrates higher accuracy, precision, CCC, and limits of agreement than the standard PE in patients when compared to MREE (2,129 +/- 45 kcal/day vs. 2,139 +/- 423 kcal/day, respectively, P = 0.1). The new equation developed to estimate REE, which takes into account both FFM and BW, provides better results than currently available equations.

Whole-Brain Voxel-Based Morphometry in Kallmann Syndrome Associated with Mirror Movements

BACKGROUND AND PURPOSE: There are 2 main hypotheses concerning the cause of mirror movements (MM) in Kallmann syndrome (KS): abnormal development of the primary motor system, involving the ipsilateral corticospinal tract, and lack of contralateral motor cortex inhibitory mechanisms, mainly through the corpus callosum. The purpose of our study was to determine white and gray matter volume changes in a KS population by using optimized voxel-based morphometry (VBM) and to investigate the relationship between the abnormalities and the presence of MM, addressing the 2 mentioned hypotheses. MATERIALS AND METHODS: T1-weighted volumetric images from 21 patients with KS and 16 matched control subjects were analyzed with optimized VBM. Images were segmented and spatially normalized, and these deformation parameters were then applied to the original images before the second segmentation. Patients were divided into groups with and without MM, and a t test statistic was then applied on a voxel-by-voxel basis between the groups and controls to evaluate significant differences. RESULTS: When considering our hypothesis a priori, we found that 2 areas of increased gray matter volume, in the left primary motor and sensorimotor cortex, were demonstrated only in patients with MM, when compared with healthy controls. Regarding white matter alterations, no areas of altered volume involving the corpus callosum or the projection of the corticospinal tract were demonstrated. CONCLUSION: The VBM study did not show significant white matter changes in patients with KS but showed gray matter alterations in keeping with a hypertrophic response to a deficient pyramidal decussation in patients with MM. In addition, gray matter alterations were observed in patients without MM, which can represent more complex mechanisms determining the presence or absence of this symptom.

Precise Insertion of Orthodontic Miniscrews with a Stereolithographic Surgical Guide Based on Cone Beam Computed Tomography Data: A Pilot Study

Purpose: Orthodontic miniscrews are commonly used to achieve absolute anchorage during tooth movement. One of the most frequent complications is screw loss as a result of root contact. Increased precision during the process of miniscrew insertion would help prevent screw loss and potential root damage, improving treatment outcomes. Stereo lithographic surgical guides have been commonly used for prosthetic implants to increase the precision of insertion. The objective of this paper was to describe the use of a stereolithographic surgical guide suitable for one-component orthodontic miniscrews based on cone beam computed tomography (CBCT) data and to evaluate implant placement accuracy. Materials and Methods: Acrylic splints were adapted to the dental arches of four patients, and six radiopaque reference points were filled with gutta-percha. The patients were submitted to CBCT while they wore the occlusal splint. Another series of images was captured with the splint alone. After superimposition and segmentation, miniscrew insertion was simulated using planning software that allowed the user to check the implant position in all planes and in three dimensions. In a rapid-prototyping machine, a stereolithographic guide was fabricated with metallic sleeves located at the insertion points to allow for three-dimensional control of the pilot bur. The surgical guide was worn during surgery. After implant insertion, each patient was submitted to CBCT a second time to verify the implant position and the accuracy of the placement of the miniscrews. Results: The average differences between the planned and inserted positions for the ten miniscrews were 0.86 mm at the coronal end, 0.71 mm at the center, and 0.87 mm at the apical tip. The average angular discrepancy was 1.76 degrees. Conclusions: The use of stereolithographic surgical guides based on CBCT data allows for accurate orthodontic mini screw insertion without damaging neighboring anatomic structures. INT J ORAL MAXILLOFAC IMPLANTS 2011;26:860-865

Energy expenditure during 2nd week of an ultra-endurance run around Australia

Purpose: For ultra-endurance athletes, whose energy expenditure is likely to be at the extremes of human tolerance for sustained periods of time, there is increased concern regarding meeting energy needs. Due to the lack of data outlining the energy requirements of such athletes, it is possible that those participating in ultra-endurance exercise are compromising performance, as well as health, as a result of inadequate nutrition and energy intake. To provide insight into this dilemma, we have presented a case study of a 37-yr-old ultra-marathon runner as he runs around the coast of Australia. Methods: Total energy expenditure was measured over a 2-wk period using the doubly labeled water technique. Results: The average total energy expenditure of the case subject was 6321 kcal.d(-1). Based on the expected accuracy and precision of the doubly labeled water technique the subject's total energy expenditure might range between 6095 and 6550 kcal.d(-1). The subject's average daily water turnover was 6.083 L over the 14-d period and might range between 5.9 L and 6.3 L.d(-1). Conclusions: This information will provide a guide to the energy requirements of ultra-endurance running and enable athletes, nutritionists, and coaches to optimize performance without compromising the health of the participant.

MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.

Pectus Excavatum postsurgical outcome based on preoperative soft body dynamics simulation

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which an abnormal formation of the rib cage gives the chest a caved-in or sunken appearance. Today, the surgical correction of this deformity is carried out in children and adults through Nuss technic, which consists in the placement of a prosthetic bar under the sternum and over the ribs. Although this technique has been shown to be safe and reliable, not all patients have achieved adequate cosmetic outcome. This often leads to psychological problems and social stress, before and after the surgical correction. This paper targets this particular problem by presenting a method to predict the patient surgical outcome based on pre-surgical imagiologic information and chest skin dynamic modulation. The proposed approach uses the patient pre-surgical thoracic CT scan and anatomical-surgical references to perform a 3D segmentation of the left ribs, right ribs, sternum and skin. The technique encompasses three steps: a) approximation of the cartilages, between the ribs and the sternum, trough b-spline interpolation; b) a volumetric mass spring model that connects two layers - inner skin layer based on the outer pleura contour and the outer surface skin; and c) displacement of the sternum according to the prosthetic bar position. A dynamic model of the skin around the chest wall region was generated, capable of simulating the effect of the movement of the prosthetic bar along the sternum. The results were compared and validated with patient postsurgical skin surface acquired with Polhemus FastSCAN system

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

Interlimb relation during the double support phase of gait: an electromyographic, mechanical and energy based analysis

The purpose of this study is to analyse the interlimb relation and the influence of mechanical energy on metabolic energy expenditure during gait. In total, 22 subjects were monitored as to electromyographic activity, ground reaction forces and VO2 consumption (metabolic power) during gait. The results demonstrate a moderate negative correlation between the activity of tibialis anterior, biceps femoris and vastus medialis of the trailing limb during the transition between midstance and double support and that of the leading limb during double support for the same muscles, and between these and gastrocnemius medialis and soleus of the trailing limb during double support. Trailing limb soleus during the transition between mid-stance and double support was positively correlated to leading limb tibialis anterior, vastus medialis and biceps femoris during double support. Also, the trailing limb centre of mass mechanical work was strongly influenced by the leading limbs, although only the mechanical power related to forward progression of both limbs was correlated to metabolic power. These findings demonstrate a consistent interlimb relation in terms of electromyographic activity and centre of mass mechanical work, being the relations occurred in the plane of forward progression the more important to gait energy expenditure.

A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica