Deformable Model for 3D Intramodal Nonrigid Breast Image Registration with Fiducial Skin Markers

We implemented a new approach to intramodal non-rigid 3D breast image registration. Our method uses fiducial skin markers (FSM) placed on the breast surface. After determining the displacements of FSM, finite element method (FEM) is used to distribute the markers’ displacements linearly over the entire breast volume using the analogy between the orthogonal components of the displacement field and a steady state heat transfer (SSHT). It is valid because the displacement field in x, y and z direction and a SSHT problem can both be modeled using LaPlace’s equation and the displacements are analogous to temperature differences in SSHT. It can be solved via standard heat conduction FEM software with arbitrary conductivity of surface elements significantly higher than that of volume elements. After determining the displacements of the mesh nodes over the entire breast volume, moving breast volume is registered to target breast volume using an image warping algorithm. Very good quality of the registration was obtained. Following similarity measurements were estimated: Normalized Mutual Information (NMI), Normalized Correlation Coefficient (NCC) and Sum of Absolute Valued Differences (SAVD). We also compared our method with rigid registration technique

Implementation of strip-area system model for fan-beam collimator SPECT reconstruction

We have implemented a more accurate physical system representation, a strip-area system model (SASM), for improved fan-beam collimator (FBC) SPECT reconstruction. This approach required implementation of modified ray tracing and attenuation compensation in comparison to a line-length system model (LLSM). We have compared performance of SASM with LLSM using Monte Carlo and analytical simulations of FBC SPECT from a thorax phantom. OSEM reconstruction was performed with OS=3 in a 64×64 matrix with attenuation compensation (assuming uniform attenuation of 0.13 cm ). Scatter correction and smoothing were not applied. We observe overall improvement in SPECT image bias, visual image quality and an improved hot myocardium contrast for SASM vs. LLSM. In contrast to LLSM, the sensitivity pattern artifacts are not present in the SASM reconstruction. In both reconstruction methods, cross-talk image artifacts (e.g. inverse images of the lungs) can be observed, due to the uniform attenuation map used. SASM applied to fan-beam collimator SPECT results in better image quality and improved hot target contrast, as compared to LLSM, but at the expense of 1.5-fold increase in reconstruction time. -

Finite-element method for intermodality nonrigid breast registration using external skin markers

We are developing a method using nonrigid co-registration of PET and MR breast images as a way to improve diagnostic specificity in difficult-to-interpret mammograms, and ultimately to avoid biopsy. A deformable breast model based on a finite-element method (FEM) has been employed. The EEM loads are taken as the observed intermodality displacements of several fiducial skin markers placed on the breast and visible in PET and MRI. The analogy between orthogonal components of the displacement field and the temperature differences in a steady-state heat transfer (SSHT) in solids has been adopted. The model allows estimation, throughout the breast, of the intermodality displacement field. To test our model, an elastic breast phantom with simulated internal lesions and external markers was imaged with PET and MRI. We have estimated fiducial- and target-registration errors vs. number and location of fiducials, and have shown that the SSHT approach using external fiducial markers is accurate to within ∼5 mm

Iterative finite element deformable model for nonrigid coregistration of multimodal breast images

We have developed a nonrigid registration technique applicable to breast tissue imaging. It relies on a finite element method (FEM) model and a set of fiducial skin markers (FSMs) placed on the breast surface. It can be applied for both intra- and intermodal breast image registration. The registration consists of two steps. First, location and displacements of corresponding FSM observed in both moving and target volumes are determined, and then FEM is used to distribute the FSM displacements linearly over the entire breast volume. After determining the displacements at all the mesh nodes, the moving breast volume is registered to the target breast volume using an image-warping algorithm. In the second step, to correct for any residual misregistration, displacements are estimated for a large number of corresponding surface points on the moving and the target breast images, already aligned in 3D, and our FEM model and the warping algorithm are applied again. Our non-rigid multimodality and intramodality breast image registration method yielded good quality images with target registration error comparable with pertinent imaging system spatial resolution. © 2006 IEEE

MRI/PET nonrigid breast-image registration using skin fiducial markers

We propose a finite-element method (FEM) deformable breast model that does not require elastic breast data for nonrigid PET/MRI breast image registration. The model is applicable only if the stress conditions in the imaged breast are virtually the same in PET and MRI. Under these conditions, the observed intermodality displacements are solely due the imaging/reconstruction process. Similar stress conditions are assured by use of an MRI breast-antenna replica for breast support during PET, and use of the same positioning. The tetrahedral volume and triangular surface elements are used to construct the FEM mesh from the MRI image. Our model requires a number of fiducial skin markers (FSM) visible in PET and MRI. The displacement vectors of FSMs are measured followed by the dense displacement field estimation by first distributing the displacement vectors linearly over the breast surface and then distributing them throughout the volume. Finally, the floating MRI image is warped to a fixed PET image, by using an appropriate shape function in the interpolation from mesh nodes to voxels. We tested our model on an elastic breast phantom with simulated internal lesions and on a small number of patients imaged with FSM using PET and MRI. Using simulated lesions (in phantom) and real lesions (in patients) visible in both PET and MRI, we established that the target registration error (TRE) is below two pet voxels

registration with fiducial skin markers

Deformable model for 3D intramodal nonrigid breast imag

Iterative deformable FEM model for nonrigid PET/MRI breast image coregistration

We implemented an iterative nonrigid registration algorithm to accurately combine functional (PET) and anatomical (MRI) images in 3D. Our method relies on a Finite Element Method (FEM) and a set of fiducial skin markers (FSM) placed on breast surface. The method is applicable if the stress conditions in the imaged breast are virtually the same in PET and MRI. In the first phase, the displacement vectors of the corresponding FSM observed in MRI and PET are determined, then FEM is used to distribute FSM displacements linearly over the entire breast volume. Our FEM model relies on the analogy between each of the orthogonal components of displacement field, and the temperature distribution field in a steady state heat transfer (SSHT) in solids. The problem can thus be solved via standard heat-conduction FEM software, with arbitrary conductivity of surface elements set much higher than that of volume elements. After determining the displacements at all mesh nodes, moving (MRI) breast volume is registered to target (PET) breast volume using an image-warping algorithm. In the second iteration, to correct for any residual surface and volume misregistration, a refinement process is applied to the moving image, which was already grossly aligned with the target image in 3D using FSM. To perform this process we determine a number of corresponding points on each moving and target image surfaces using a nearest-point approach. Then, after estimating the displacement vectors between the corresponding points on the surfaces we apply our SSHT model again. We tested our model on twelve patients with suspicious breast lesions. By using lesions visible in both PET and MRI, we established that the target registration error is below two PET voxels. The surface registration error is comparable to the spatial resolution of PET

Application of Ordered-Subsets Expectation- Maximization (OSEM) algorithm to cone-beam SPECT for accelerated 3D reconstruction

We investigated the performance of an ordered-subsets expectation- maximization (OSEM) algorithm for accelerated reconstruction in cone-beam SPECT. SPECT scans were performed using a Defrise phantom filled with 0.9 μCi/ml of Tc-99m and a dual-head gamma camera equipped with one cone-beam (CBC, f = 70 cm) and one parallel-beam collimator (PBC). Images were reconstructed using a fully-3D approach with resolution and attenuation modeling and an ordered-subsets version of a maximum-likelihood expectation-maximization algorithm (MLEM). Three grouping patterns of subsets were applied: consecutive, orthogonal, and uniform. In contrast to PBC SPECT, we observe that, in CBC SPECT, the reconstruction grouping pattern of the subsets is very important for the image quality obtained. Only when the projection data grouped into a subset were selected as uniformly as possible from all the acquired views, were the image quality and the noise in the images very close to results obtained using MLEM. However, we note that, for both CBC and PBC SPECT, the loglikelihood for a given iteration is practically the same for different grouping patterns of subsets. © 2004 IEEE

Maximum-likelihood expectation-maximization algorithm for improved clinical SPECT scintimammography

Conventional MLEM and OSEM algorithms used in SPECT Tc-99m sestamibi scintimammography produce hot spot artifacts (HSA). We investigated a suitable modification of MLEM and OSEM algorithms needed to reduce HSA. Patients with suspicious breast lesions were administered 10 mCi of Tc99m sestamibi and SPECT scans with patients in prone position with uncompressed breasts were acquired. In addition, to simulate breast lesions, some patients were imaged with a number of breast skin markers each containing 1 μCi of Tc-99m. We modified MLEM and OSEM algorithms by removing from the backprojection step the rays that traverse the periphery of the support region on the way to a detector bin when their path length trough this region is shorter than some preset critical length. Such very short paths result in a very low projection counts contributed to the detector bin and this in turn gives rise to a overestimation of the activity hi the peripheral voxels in the backprojection step, thus creating HSA. We analyzed the breastlesion contrast and suppression of HSA in the images reconstructed using conventional and modified MLEM and OSEM algorithms vs. critical path length (CPL). For CPL ≥ 0.01 pixel size, we observed improved breast-lesion contrast and lower noise in the images reconstructed, and a very significant reduction of HSA in the maximum intensity projection (MIP) images © 2004 IEEE