Small dense particles in the retina observable by spectral-domain optical coherence tomography in age-related macular degeneration

To observe detailed changes in neurosensory retinal structure after anti-VEGF upload in age-related macular degeneration (AMD), by using spectral domain optical coherence tomography (SD-OCT).

Spectral-domain optical coherence tomography use in macular diseases: a review

The introduction of spectral-domain optical coherence tomography (SD-OCT) has improved the clinical value for assessment of the eyes with macular disease. This article reviews the advances of SD-OCT for the diagnostic of various macular diseases. These include vitreomacular traction syndrome, cystoid macular edema/diabetic macular edema, epiretinal membranes, full-thickness macular holes, lamellar holes, pseudoholes, microholes, and schisis from myopia. Besides offering new insights into the pathogenesis of macular abnormalities, SD-OCT is a valuable tool for monitoring macular disease.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Focal cystic high-attenuation lesions: characterization in renal phantom by using photon-counting spectral CT--improved differentiation of lesion composition

To evaluate the capability of spectral computed tomography (CT) to improve the characterization of cystic high-attenuation lesions in a renal phantom and to test the hypothesis that spectral CT will improve the differentiation of cystic renal lesions with high protein content and those that have undergone hemorrhage or malignant contrast-enhancing transformation.

Effects on choroidal neovascularization after anti-VEGF Upload using intravitreal ranibizumab, as determined by spectral domain-optical coherence tomography

It is unclear whether anti-VEGF monotherapy in age-related macular degeneration (AMD) achieves morphologic CNV regression or only stops further CNV growth. In this study, spectral domain-optical coherence tomography (SD-OCT) was used to image CNV structure before and after anti-VEGF treatment.

Repeatability of nerve fiber layer thickness measurements in patients with glaucoma and without glaucoma using spectral-domain and time-domain OCT

The aim of this work is to assess the repeatability of spectral-domain-OCT (SD-OCT) retinal nerve fiber layer thickness (RNFL) thickness measurements in a non-glaucoma group and patients with glaucoma and to compare these results to conventional time-domain-OCT (TD-OCT).

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.