Synthetic computed tomography generation for abdominal adaptive radiotherapy using low-field magnetic resonance imaging.

Background And Purpose: Magnetic Resonance guided Radiotherapy (MRgRT) still needs the acquisition of Computed Tomography (CT) images and co-registration between CT and Magnetic Resonance Imaging (MRI). The generation of synthetic CT (sCT) images from the MR data can overcome this limitation. In this study we aim to propose a Deep Learning (DL) based approach for sCT image generation for abdominal Radiotherapy using low field MR images.

Bladder Wall Segmentation and Characterization on MR Images: Computer-Aided Spina Bifida Diagnosis.

(1) Background: Segmentation of the bladder inner's wall and outer boundaries on Magnetic Resonance Images (MRI) is a crucial step for the diagnosis and the characterization of the bladder state and function. This paper proposes an optimized system for the segmentation and the classification of the bladder wall. (2) Methods: For each image of our data set, the region of interest corresponding to the bladder wall was extracted using LevelSet contour-based segmentation.

Technical note: Design and initial evaluation of a novel physical breast phantom to monitor image quality in digital breast tomosynthesis.

Purpose: To describe the creation process of a new breast phantom specifically designed to monitor quality control (QC) metrics consistency over several months in digital breast tomosynthesis (DBT).

Methods: The semi-anthropomorphic Tomomam phantom was designed and evaluated twice monthly on a single Hologic Selenia Dimensions unit over 5 months. The phantom is manufactured in a one-piece epoxy resin homogeneous material as the basis for manufacturing, simulating breast tissue as 50% equivalent glandular (GL)/50% equivalent adipose (AD) and compressed thickness of 60 mm.

Multi-View Separable Pyramid Network for AD Prediction at MCI Stage by F-FDG Brain PET Imaging.

Alzheimer's Disease (AD), one of the main causes of death in elderly people, is characterized by Mild Cognitive Impairment (MCI) at prodromal stage. Nevertheless, only part of MCI subjects could progress to AD. The main objective of this paper is thus to identify those who will develop a dementia of AD type among MCI patients.

Stimulated Raman histology: one to one comparison with standard hematoxylin and eosin staining.

We present for the first time one-to-one correspondence between standard hematoxylin/eosin (H&E) stained tissue sections and stimulated Raman histology (SRH) - a label-free technique in which stimulated Raman scattering (SRS) and second harmonic generation (SHG) are combined to generate virtual H&E images. Experiments were performed on both human thin cryogenic slides from the gastrointestinal tract (GI) and thick freshly excised biopsies from endoscopic surgery. Results on cryogenic slides evidenced an excellent agreement between SRH and H&E images while the ones on biopsies established the relevance of SRH for rapid intraoperative histology to assist in surgical decision making.

Multiscale spatial gradient features for F-FDG PET image-guided diagnosis of Alzheimer's disease.

Background And Objective: F-FluoroDeoxyGlucose Positron Emission Tomography (F-FDG PET) is one of the imaging biomarkers to diagnose Alzheimer's Disease (AD). In F-FDG PET images, the changes of voxels' intensities reflect the differences of glucose rates, therefore voxel intensity is usually used as a feature to distinguish AD from Normal Control (NC), or at earlier stage to distinguish between progressive and stable Mild Cognitive Impairment (pMCI and sMCI). In this paper, F-FDG PET images are characterized in an alternative way-the spatial gradient, which is motivated by the observation that the changes of F-FDG rates also cause gradient changes.

Fast stimulated Raman and second harmonic generation imaging for intraoperative gastro-intestinal cancer detection.

Conventional haematoxylin, eosin and saffron (HES) histopathology, currently the 'gold-standard' for pathological diagnosis of cancer, requires extensive sample preparations that are achieved within time scales that are not compatible with intra-operative situations where quick decisions must be taken. Providing to pathologists a close to real-time technology revealing tissue structures at the cellular level with HES histologic quality would provide an invaluable tool for surgery guidance with evident clinical benefit. Here, we specifically develop a stimulated Raman imaging based framework that demonstrates gastro-intestinal (GI) cancer detection of unprocessed human surgical specimens.