A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria.

Recent studies reveal that mitochondria take substantial responsibility in cellular functions that are closely related to aging diseases caused by degeneration of neurons. These studies emphasize that the membrane and crista morphology of a mitochondrion should receive attention in order to investigate the link between mitochondrial function and its physical structure. Electron microscope tomography (EMT) allows analysis of the inner structures of mitochondria by providing highly detailed visual data from large volumes.

Bayesian segmentation of human facial tissue using 3D MR-CT information fusion, resolution enhancement and partial volume modelling.

Background: Accurate segmentation of human head on medical images is an important process in a wide array of applications such as diagnosis, facial surgery planning, prosthesis design, and forensic identification.

Objectives: In this study, a Bayesian method for segmentation of facial tissues is presented. Segmentation classes include muscle, bone, fat, air and skin.

Automatic segmentation of human facial tissue by MRI-CT fusion: a feasibility study.

The aim of this study was to develop automatic image segmentation methods to segment human facial tissue which contains very thin anatomic structures. The segmentation output can be used to construct a more realistic human face model for a variety of purposes like surgery planning, patient specific prosthesis design and facial expression simulation. Segmentation methods developed were based on Bayesian and Level Set frameworks, which were applied on three image types: magnetic resonance imaging (MRI), computerized tomography (CT) and fusion, in which case information from both modalities were utilized maximally for every tissue type.

Image analysis for cystic fibrosis: computer-assisted airway wall and vessel measurements from low-dose, limited scan lung CT images.

Cystic fibrosis (CF) is a life-limiting genetic disease that affects approximately 30,000 Americans. When compared to those of normal children, airways of infants and young children with CF have thicker walls and are more dilated in high-resolution computed tomographic (CT) imaging. In this study, we develop computer-assisted methods for assessment of airway and vessel dimensions from axial, limited scan CT lung images acquired at low pediatric radiation doses.

Computerized scar detection on renal cortical scintigraphy images.

Objective: Renal cortical scintigraphy is a well-established functional imaging technique for visual analysis of radiopharmaceutical tracer distribution. However, the visual evaluation is subjective, causing interobserver variability, especially in a quantifiable number of scars. The purpose of this study was to develop new computerized methods in renal cortical scintigraphy image interpretation, particularly addressing activity distribution and cortex continuity (scars).

Development of a visio-haptic integrated dental training simulation system.

The use of haptic devices in the medical field has become widespread in the last decade. In this study, a visio-haptic dental training system is developed using haptic and stereoscopic devices. Several advantages are offered by such a simulation system, including effective learning without any fear of making mistakes on a patient, possibility of repeating various dental operations, ease of evaluating student performance, and low-cost dental training even without an instructor.

Image analysis for cystic fibrosis: automatic lung airway wall and vessel measurement on CT images.

Cystic Fibrosis (CF) is the most common lethal genetic disorder in the Caucasian population, affecting about 30,000 people in the United States. It results in inflammation, hence thickening of airway (AW) walls. It has been demonstrated that AW inflammation begins early in life producing structural AW damage.

SVM-based detection of distant protein structural relationships using pairwise probabilistic suffix trees.

A new method based on probabilistic suffix trees (PSTs) is defined for pairwise comparison of distantly related protein sequences. The new definition is adopted in a discriminative framework for protein classification using pairwise sequence similarity scores in feature encoding. The framework uses support vector machines (SVMs) to separate structurally similar and dissimilar examples.

A discriminative method for remote homology detection based on n-peptide compositions with reduced amino acid alphabets.

In this study, n-peptide compositions are utilized for protein vectorization over a discriminative remote homology detection framework based on support vector machines (SVMs). The size of amino acid alphabet is gradually reduced for increasing values of n to make the method to conform with the memory resources in conventional workstations. A hash structure is implemented for accelerated search of n-peptides.

Simultaneous surface registration of ictal and interictal SPECT and magnetic resonance images for epilepsy studies.

Background: Subtraction of ictal and interictal single photon emission computed tomography (SPECT) images is known to be successful in localizing the seizure focus in the pre-surgical evaluation of patients with partial epilepsy. A computer-aided methods for producing subtraction ictal SPECT co-registered to the magnetic resonance image (MRI) (the SISCOM method) is commonly used. The two registrations involved in SISCOM are (1) between the ictal-interictal SPECT images, which was shown to be the more critical, and (2) between the ictal image and MRI.

Sampling of sentinel lymph nodes: a simulation study.

Objective: To analyze the effects of various slicing schemes on the detection of metastases in lymph nodes.

Study Design: Use of an advanced computer simulation tool.

Results: Bisectioning along the longitudinal axis is an inadequate approach.