Coupled s-excess HMM for vessel border tracking and segmentation.

In this paper, we present a novel image segmentation technique, based on hidden Markov model (HMM), which we then apply to simultaneously segment interior and exterior walls of fluorescent confocal images of lymphatic vessels. Our proposed method achieves this by tracking hidden states, which are used to indicate the locations of both the inner and outer wall borders throughout the sequence of images. We parameterize these vessel borders using radial basis functions (RBFs), thus enabling us to minimize the number of points we need to track as we progress through multiple layers and therefore reduce computational complexity. Information about each border is detected using patch-wise convolutional neural networks (CNN). We use the softmax function to infer the emission probability and use a proposed new training algorithm based on s-excess optimization to learn the transition probability. We also introduce a new optimization method to determine the optimum sequence of the hidden states. Thus, we transform the segmentation problem into one that minimizes an s-excess graph cut, where each hidden state is represented as a graph node and the weight of these nodes are defined by their emission probabilities. The transition probabilities are used to define relationships between neighboring nodes in the constructed graph. We compare our proposed method to the Viterbi and Baum-Welch algorithms. Both qualitative and quantitative analysis show superior performance of the proposed methods.

Automatic segmentation of lymph vessel wall using optimal surface graph cut and hidden Markov Models.

We present a novel method to segment the lymph vessel wall in confocal microscopy images using Optimal Surface Segmentation (OSS) and hidden Markov Models (HMM). OSS is used to preform a pre-segmentation on the images, to act as the initial state for the HMM. We utilize a steerable filter to determine edge based filters for both of these segmentations, and use these features to build Gaussian probability distributions for both the vessel walls and the background. From this we infer the emission probability for the HMM, and the transmission probability is learned using a Baum-Welch algorithm. We transform the segmentation problem into one of cost minimization, with each node in the graph corresponding to one state, and the weight for each node being defined using its emission probability. We define the inter-relations between neighboring nodes using the transmission probability. Having constructed the problem, it is solved using the Viterbi algorithm, allowing the vessel to be reconstructed. The optimal solution can be found in polynomial time. We present qualitative and quantitative analysis to show the performance of the proposed method.

Combining region-based and imprecise boundary-based cues for interactive medical image segmentation.

In this paper, we present an approach combining both region selection and user point selection for user-assisted segmentation as either an enclosed object or an open curve, investigate the method of image segmentation in specific medical applications (user-assisted segmentation of the media-adventitia border in intravascular ultrasound images, and lumen border in optical coherence tomography images), and then demonstrate the method with generic images to show how it could be utilized in other types of medical image and is not limited to the applications described. The proposed method combines point-based soft constraint on object boundary and stroke-based regional constraint. The user points act as attraction points and are treated as soft constraints rather than hard constraints that the segmented boundary has to pass through. The user can also use strokes to specify region of interest. The probabilities of region of interest for each pixel are then calculated, and their discontinuity is used to indicate object boundary. The combinations of different types of user constraints and image features allow flexible and robust segmentation, which is formulated as an energy minimization problem on a multilayered graph and is solved using a shortest path search algorithm. We show that this combinatorial approach allows efficient and effective interactive segmentation, which can be used with both open and closed curves to segment a variety of images in different ways. The proposed method is demonstrated in the two medical applications, that is, intravascular ultrasound and optical coherence tomography images, where image artefacts such as acoustic shadow and calcification are commonplace and thus user guidance is desirable. We carried out both qualitative and quantitative analysis of the results for the medical data; comparing the proposed method against a number of interactive segmentation techniques.

A mechanism of ryanodine receptor modulation by FKBP12/12.6, protein kinase A, and K201.

AIMS: Our objective was to explore the functional interdependence of protein kinase A (PKA) phosphorylation with binding of modulatory FK506 binding proteins (FKBP12/12.6) to the ryanodine receptor (RyR). RyR type 1 or type 2 was prepared from rabbit skeletal muscle or pig cardiac muscle, respectively. In heart failure, RyR2 dysfunction is implicated in fatal arrhythmia and RyR1 dysfunction is associated with muscle fatigue. A controversial underlying mechanism of RyR1/2 dysfunction is proposed to be hyperphosphorylation of RyR1/2 by PKA, causing loss of FKBP12/12.6 binding that is reversible by the experimental inhibitory drug K201 (JTV519). Phosphorylation is also a trigger for fatal arrhythmia in catecholaminergic polymorphic ventricular tachycardia associated with point mutations in RyR2. METHODS AND RESULTS: Equilibrium binding kinetics of RyR1/2 to FKBP12/12.6 were measured using surface plasmon resonance (Biacore). Free Ca(2+) concentration was used to modulate the open/closed conformation of RyR1/2 channels measured using [(3)H]ryanodine binding assays. The affinity constant-K(A), for RyR1/2 binding to FKBP12/12.6, was significantly greater for the closed compared with the open conformation. The effect of phosphorylation or K201 was to reduce the K(A) of the closed conformation by increasing the rate of dissociation k(d). K201 reduced [(3)H]ryanodine binding to RyR1/2 at all free Ca(2+) concentrations including PKA phosphorylated preparations. CONCLUSION: The results are explained through a model proposing that phosphorylation and K201 acted similarly to change the conformation of RyR1/2 and regulate FKBP12/12.6 binding. K201 stabilized the conformation, whereas phosphorylation facilitated a subsequent molecular event that might increase the rate of an open/closed conformational transition.

Ryanodine receptor binding to FKBP12 is modulated by channel activation state.

Ryanodine receptor (RyR) Ca2+ release channels undergo a conformational change between the open and closed states. Its protein modulator, FK506 binding protein 12 (FKBP12), stabilises the channel gating between the four subunits that surround a central Ca2+-conducting pore. To understand the interdependence of RyR and FKBP12 binding, physiological and pharmacological agents were used to modulate the RyR open/closed state. ELISA sandwich binding assays showed that FKBP12 binding was dependent on the free Ca2+ and was lower at 1-10 microM free Ca2+ compared with 1 mM EGTA and 1 mM Ca2+, and this effect was enhanced by the inclusion of 1 mM ATP. Ruthenium red increased the binding of FKBP12. [3H]Ryanodine binding confirmed that 1 mM EGTA, 1 mM Ca2+ and 1 microM ruthenium red closed the channel, whereas 1 microM free Ca2+, 1 microM free Ca2+ + 1 mM ATP, or 10 mM caffeine opened it. These binding conditions were used in surface plasmon resonance studies to measure equilibrium binding kinetics. The affinity constant KA was significantly greater for the closed than the open channel, a change mediated by a decreased dissociation rate constant, kd. The results show that surface plasmon resonance is a powerful technique that can measure differences in RyR1 equilibrium binding kinetics with FKBP12.