Proceedings IEEE International Symposium on Biomedical Imaging

We propose a methodology for brain parcellation with anatomical and functional constraints dedicated to fMRI data analysis. The aim is to provide a representation of fMRI data at any intermediate dimensionality between voxel and region of interest. In order to fill in the gap between these two approaches we developed an automatic parcellation of the 3D cortex with an adjustable resolution. The algorithm relies on an adaptation of the K-means clustering in a non convex domain with geodesic distances. Fine anatomical or functional constraints can be embedded through the use of weighted geodesic distances. The applications of such a method are principally connectivity studies, multivariate analyses and fusion with other modalities.

Develops an innovative image reconstruction technique for reflection tomography based upon the extraction of multiple-bounce (MB) ghosting artifacts. The basic concept is that the time-of-flight between the transmission and reception of a waveform includes the realistic effects of MB interactions. An enhanced quality image can be constructed by utilizing only the single-bounce (SB) contributions of the measured time-of-flight projection data. In addition, the MB ghosting artifacts are projected into a series of auxiliary images that can be applied to enhance performance of object identification. These novel methods can be applied to any domain of medical imaging which is based upon the concepts of reflection tomography, such as ultrasound.

In this paper, a high resolution segmentation method for MR images of mouse heart chambers is developed, in which the EM algorithm is adopted and extended to the spatio-temporal cardiac cycle, and a partial pixel effect (PPE) is accommodated so that the heart chambers boundary is detected to sub-pixel accuracy. The method has been tested on high and low spatial resolution images. Quantitative measurements of the left ventricle (LV) area-time curve over cardiac cycle are reported, which show that the accuracy of the LV area can be improved based on the new method, on low spatial resolution images. The average relative error of the area estimate of the new method applied to low resolution images relative to measurements on high resolution images is less than 8%.

We present a new method for reconstructing digitally recorded off-axis Fresnel holograms. Currently-used reconstruction methods are based on the simulation and propagation of a reference wave that is diffracted by the hologram. This procedure introduces a twin-image and a zero-order term which are inherent to the diffraction phenomenon. These terms perturb the reconstruction and limit the field of view. Our new approach splits the reconstruction process into two parts. First, we recover the amplitude and the phase in the camera plane from the measured hologram intensity. Our algorithm is based on the hypothesis of a slowly varying object wave which interferes with a more rapidly varying reference wave. In a second step, we propagate this complex wave to refocus it using the Fresnel transform. We therefore avoid the presence of the twin-image and zero-order interference terms. This new approach is flexible and can be adapted easily to complicated experimental setups. We demonstrate its feasibility in the case of digital holographic microscopy and present results for the imaging of living neurons.

The motion of coronary arteries has attracted increasing attention because of its possible effects on the development of atherosclerosis. Biplane angiography is the best clinical modality so far to extract this information spatially and temporally. In this paper, a new method is proposed to track 3-D coronary artery segments in biplane angiogram sequences based on a 3-D deformable model. The model combines the 3-D active contour model with image block matching technique, and considers both global and local motion of the vessel. By this new method, the coronary artery segment can be tracked well over a cardiac cycle.

Model-based approaches towards the segmentation of vascular and cardiac images are presented. For vessel segmentation, prior shape information is introduced based on the notion that vessels are elongated structures. For cardiac segmentation, shape information derived from a training set of segmented images is incorporated in an automatically constructed point distribution model of the heart.

We show results for full three-dimensional nonlinear inversion of the parameters of a diffusive partial differential equation, specifically for an optical tomography application. We compute functional derivatives of the parameters with respect to the mean-squared error using the adjoint field method, and implement two forms of regularization. In the first, a penalty term is introduced into the error functional, and in the second, the solution to the inverse problem is assumed to belong to a parametrized class of functions. In the case where this assumption is correct, our results demonstrate that the parameters can recovered with high accuracy, yielding a better inversion result than the traditional Tikhonov-type approach.

We investigate support vector machines (SVM) in the context of oral lesion classification using digital color images as input. Two common lesions of similar visual appearance to the human observer were evaluated: oral leukoplakia, which is a potentially pre-cancerous lesion, and oral lichenoid reactions (with subclasses of atrophic, plaqueformed and reticular reactions), which are usually harmless lesions. In total, 89% (212 out of 238, 5-fold CV) were correctly classified in a two-class problem (precancerous vs. non-pre-cancerous) and 78% (61 out of 78, hold-out) into four classes (complete classification). The proposed method can be used as a decision support tool in CADx systems for oral lesion classification and detection of potentially pre-cancerous lesions.

Target specific MRI poses special opportunities and challenges. Although MRI can provide exquisite morphologic details, its relatively low sensitivity has severely hampered the development of target-specific contrast agents that can provide enough signal alteration to be detectable in vivo. In this review, we will present our data on the development of polymerized vesicles for use in vascular-targeted imaging using MRI. Because of the high amount of payload that can be carried to the target site via these particles, they can be detectable with MRI. In addition, the same platform can be used for delivering multiple different types of contrast ions as well as therapeutic agents to vascular target sites. We believe that by using the same platform for imaging and therapy, we can have an accurate way of personalizing treatment.

Micro-CT X-quang đã trở thành điểm nhấn trong phòng thí nghiệm CT/Micro-CT tại Đại học Iowa. Trong bài báo này, chúng tôi mô tả một số tiến bộ gần đây mà chúng tôi đã đạt được trong lĩnh vực micro-CT chùm tia hình nón. Đầu tiên, chúng tôi đề cập đến việc tái tạo xấp xỉ sử dụng các thuật toán loại Feldkamp với nhiều nguồn X-quang và cấu hình cảm biến bị lệch. Sau đó, chúng tôi giải thích ba loại artefact liên quan đến tái tạo chính xác trong khuôn khổ Grangeat. Cuối cùng, chúng tôi báo cáo về sự hội tụ của một sơ đồ Landweber dạng khối tổng quát. Các hình ảnh đại diện từ mô phỏng và thí nghiệm cũng được trình bày.