Tobias Lasser

Free-space fluorescence molecular tomography utilizing 360° geometry projections

Fluorescence tomography of diffuse media can yield optimal three-dimensional imaging when multiple projections over 360° geometries are captured, compared with limited projection angle systems such as implementations in the slab geometry. We demonstrate how it is possible to perform noncontact, 360° projection fluorescence tomography of mice using CCD-camera-based detection in free space, i.e., in the absence of matching fluids. This approach achieves high spatial sampling of photons propagating through tissue and yields a superior information content data set compared with fiber-based 360° implementations. Reconstruction feasibility using 36 projections in 10° steps is demonstrated in mice.

Towards intra-operative 3D nuclear imaging: reconstruction of 3D radioactive distributions using tracked gamma probes

Nuclear medicine imaging modalities assist commonly in surgical guidance given their functional nature. However, when used in the operating room they present limitations. Pre-operative tomographic 3D imaging can only serve as a vague guidance intra-operatively, due to movement, deformation and changes in anatomy since the time of imaging, while standard intra-operative nuclear measurements are limited to 1D or (in some cases) 2D images with no depth information. To resolve this problem we propose the synchronized acquisition of position, orientation and readings of gamma probes intra-operatively to reconstruct a 3D activity volume. In contrast to conventional emission tomography, here, in a first proof-of-concept, the reconstruction succeeds without requiring symmetry in the positions and angles of acquisition, which allows greater flexibility. We present our results in phantom experiments for sentinel node lymph node localization. The results indicate that 3D intra-operative nuclear images can be generated in such a setup up to an accuracy equivalent to conventional SPECT systems. This technology has the potential to advance standard procedures towards intra-operative 3D nuclear imaging and offers a novel approach for robust and precise localization of functional information to facilitate less invasive, image-guided surgery.

X-Ray Tensor Tomography

Here we introduce a new concept for x-ray computed tomography that yields information about the local micro-morphology and its orientation in each voxel of the reconstructed 3D tomogram. Contrary to conventional x-ray CT, which only reconstructs a single scalar value for each point in the 3D image, our approach provides a full scattering tensor with multiple independent structural parameters in each volume element. In the application example shown in this study, we highlight that our method can visualize sub-pixel fiber orientations in a carbon composite sample, hence demonstrating its value for non-destructive testing applications. Moreover, as the method is based on the use of a conventional x-ray tube, we believe that it will also have a great impact in the wider range of material science investigations and in future medical diagnostics.

EndoTOFPET-US: a novel multimodal tool for endoscopy and positron emission tomography

The EndoTOFPET-US project aims to develop a multimodal detector to foster the development of new biomarkers for prostate and pancreatic tumors. The detector will consist of two main components: an external plate, and a PET extension to an endoscopic ultrasound probe. The external plate is an array of LYSO crystals read out by silicon photomultipliers (SiPM) coupled to an Application Specific Integrated Circuit (ASIC). The internal probe will be an highly integrated and miniaturized detector made of LYSO crystals read out by a fully digital SiPM featuring photosensor elements and digital readout in the same chip. The position and orientation of the two detectors will be tracked with respect to the patient to allow the fusion of the metabolic image from the PET and the anatomic image from the ultrasound probe in the time frame of the medical procedure. The fused information can guide further interventions of the organ, such as biopsy or in vivo confocal microscopy.

Real-time fusion of ultrasound and gamma probe for navigated localization of liver metastases

Liver metastases are an advanced stage of several types of cancer, usually treated with surgery. Intra-operative localization of these lesions is currently facilitated by intra-operative ultrasound (IOUS) and palpation, yielding a high rate of false positives due to benign abnormal regions. In this paper we present the integration of functional nuclear information from a gamma probe with IOUS, to provide a synchronized, real-time visualization that facilitates the detection of active metastases intra-operatively. We evaluate the system in an ex-vivo setup employing a group of physicians and medical technicians and show that the addition of functional imaging improves the accuracy of localizing and identifying malignant and benign lesions significantly. Furthermore we are able to demonstrate that the inclusion of an advanced, augmented visualization provides more reliability and confidence on classifying these lesions in the presented evaluation setup.

Mini gamma cameras for intra-operative nuclear tomographic reconstruction

Nuclear imaging modalities like PET or SPECT are in extensive use in medical diagnostics. In a move towards personalized therapy, we present a flexible nuclear tomographic imaging system to enable intra-operative SPECT-like 3D imaging. The system consists of a miniaturized gamma camera mounted on a robot arm for flexible positioning, while spatio-temporal localization is provided by an optical tracking system. To facilitate statistical tomographic reconstruction of the radiotracer distribution using a maximum likelihood approach, a precise model of the mini gamma camera is generated by measurements. The entire system is evaluated in a series of experiments using a hot spot phantom, with a focus on criteria relevant for the intra-operative workflow, namely the number of required imaging positions as well as the required imaging time. The results show that high quality reconstructed images of simple hot spot configurations with positional errors of less than one millimeter are possible within acquisition times as short as 15s.

Trajectory optimization for intra-operative nuclear tomographic imaging

Diagnostic nuclear imaging modalities like SPECT typically employ gantries to ensure a densely sampled geometry of detectors in order to keep the inverse problem of tomographic reconstruction as well-posed as possible. In an intra-operative setting with mobile freehand detectors the situation changes significantly, and having an optimal detector trajectory during acquisition becomes critical. In this paper we propose an incremental optimization method based on the numerical condition of the system matrix of the underlying iterative reconstruction method to calculate optimal detector positions during acquisition in real-time. The performance of this approach is evaluated using simulations. A first experiment on a phantom using a robot-controlled intra-operative SPECT-like setup demonstrates the feasibility of the approach.

Out-of-plane artifact reduction in tomosynthesis based on regression modeling and outlier detection

We propose a method for out-of-plane artifact reduction in digital breast tomosynthesis reconstruction. Because of the limited angular range acquisition in DBT, the reconstructed slices have reduced resolution in z-direction and are affected by artifacts. The out-of-plane blur caused by dense tissue and large masses complicates reconstruction of thick slices volumes. The streak-like out-of-plane artifacts caused by calcifications and metal clips distort the shape of calcifications which is regarded by many radiologists as an important malignancy predictor. Small clinical features such as micro-calcifications could be obscured by bright artifacts. The proposed technique involves reconstructing a set of super-resolution slices and predicting the artifact-free voxel intensity based on the corresponding set of projection pixels using a statistical model learned from a set of training data. Our experiments show that the resulting reconstructed images are de-blurred and streak-like artifacts are reduced, visibility of clinical features, contrast and sharpness are improved and thick-slice reconstruction is possible without the loss of contrast and sharpness.

Computer---Aided diagnosis of pigmented skin dermoscopic images

Diagnosis of benign and malign skin lesions is currently mostly relying on visual assessment and frequent biopsies performed by dermatologists. As the timely and correct diagnosis of these skin lesions is one of the most important factors in the therapeutic outcome, leveraging new technologies to assist the dermatologist seems natural. In this paper we propose a machine learning approach to classify melanocytic lesions into malignant and benign from dermoscopic images. The dermoscopic image database is composed of 4240 benign lesions and 232 malignant melanoma. For segmentation we are using multiphase soft segmentation with total variation and H1 regularization. Then, each lesion is characterized by a feature vector that contains shape, color and texture information, as well as local and global parameters that try to reflect structures used in medical diagnosis. The learning and classification stage is performed using SVM with polynomial kernels. The classification delivered accuracy of 98.57% with a true positive rate of 0.991% and a false positive rate of 0.019%.

First Use of Mini Gamma Cameras for Intra-operative Robotic SPECT Reconstruction

Different types of nuclear imaging systems have been used in the past, starting with pre-operative gantry-based SPECT systems and gamma cameras for 2D imaging of radioactive distributions. The main applications are concentrated on diagnostic imaging, since traditional SPECT systems and gamma cameras are bulky and heavy. With the development of compact gamma cameras with good resolution and high sensitivity, it is now possible to use them without a fixed imaging gantry. Mounting the camera onto a robot arm solves the weight issue, while also providing a highly repeatable and reliable acquisition platform. In this work we introduce a novel robotic setup performing scans with a mini gamma camera, along with the required calibration steps, and show the first SPECT reconstructions. The results are extremely promising, both in terms of image quality as well as reproducibility. In our experiments, the novel setup outperformed a commercial fhSPECT system, reaching accuracies comparable to state-of-the-art SPECT systems.