A Survey on Deep Learning in Medical Image Analysis

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area. Open challenges and directions for future research are discussed.Comment: Revised survey includes expanded discussion section and reworked introductory section on common deep architectures. Added missed papers from before Feb 1st 201

A Novel Approach for the Visualisation and Progression Tracking of Metastatic Bone Disease

Metastatic bone disease (MBD) is a common secondary feature of cancer that can cause significant complications, including severe pain and death. Current methods of diagnosis require a highly trained radiologist capable of interpreting medical images and recognising the sites of MBD. These medical images are often noisy, two dimensional, greyscale and usually have a poor resolution. In order to help assist with these issues, several studies have shown that computer aided methods can locate MBD within medical images. However these methods are limited in scope, accuracy, sensitivity, explainability and do not improve upon the poor visualisations of the underlying medical imaging data. To address these limitations, I have developed a novel method of automatic MBD assessment and visualisation using computed tomography (CT) imaging data as the input. The method is fully automated and does not require any human interaction -- although users can interact with a viewer that visualises the results. This method has been tested on CT data from prostate cancer patients as prostate cancer is one of the most common sources of MBD. The method described in this thesis has a sensitivity of 0.871 when detecting sclerotic and lytic lesions within a single data set. This sensitivity is comparable to existing methods, however the scope in detecting these lesions was limited to the vertebrae in previous studies. My method significantly expands this scope to include the ribs, vertebrae, pelvis and proximal femurs. The work in this thesis also provides novel visualisations of the disease and does not suffer from explainability issues that plague modern machine learning algorithms. In addition, I developed a novel method of tracking the spread of MBD at multiple time points using longitudinal CT data. This method is capable of calculating the change in lesion volume size across multiple time points, providing a novel numerical assessment.The Armstrong Trus

On prediction of the compressive strength and failure patterns of human vertebrae using a quasi-brittle continuum damage finite element model

International audienc

Comparison of Surgical Outcomes of the Posterior and Combined Approaches for Repair of Cervical Fractures in Ankylosing Spondylitis.

STUDY DESIGN: Retrospective cohort study. PURPOSE: To evaluate surgical outcomes and complications of cervical spine fractures in ankylosing spondylitis (CAS) patients who were treated using either the posterior (P) or combined approach (C). OVERVIEW OF LITERATURE: Ankylosing spondylitis typically causes progressive spinal stiffness that makes patients susceptible to spinal fractures. CAS is a highly unstable condition. There is contradictory evidence regarding which treatment option, the posterior or the combined approach, yields superior clinical results. METHODS: A single institution database was reviewed for data in the period 1999 to 2015. All CAS patients who underwent posterior or combined instrumented fusion were enrolled. We analyzed demographic data, radiographic results, perioperative complications, and postoperative results. RESULTS: Thirty-three patients were enrolled (23 in the P group, 10 in the C group). All patients presented with neck pain after a fall. In the P group, mean operative time was 161.1 minutes (100-327 minutes), and mean estimated blood loss (EBL) was 306.4 mL (50-750 mL). In the C group, 90% of patients underwent a staged procedure, typically with posterior surgery first. Mean EBL was 124 mL (25-337 mL). For posterior surgery, mean EBL was 458.3 mL (400-550 mL). EBL of posterior surgery in the C group was higher but this difference was not significant (p=0.16). Postoperative complication rate was higher in the C group but this difference was not significant (50% vs. 17.4%, p=0.09). In the follow-up period, no late reoperations were performed. Patients who underwent C surgery had a higher rate of neurological improvement but this difference was not significant (p=0.57). CONCLUSIONS: Both P and C provided good clinical results. P surgery had lower EBL, lower postoperative complication rate, and shorter length of stay than C surgery; none of these differences were statistically significant

Accuracy of CT-based attenuation correction in bone imaging with PET/CT

Proceeding of: 2007 IEEE Nuclear Science Symposium Conference Record (NSS'07), Honolulu, Hawaii, USA, Oct. 27 - Nov. 3, 2007PET/CT has become the most comprehensive diagnostic tool in oncology imaging providing improved lesion identification and localization. Bone is a common site of metastasis and the quantitative accuracy of PET images in bone tissue is important for assessing response to therapy. The use of CT images for attenuation correction is becoming a standard procedure in these scanners. However the impact of CT-based attenuation correction (CTAC) on the accuracy of PET tracer uptake values measured in bone has not been carefully evaluated, having only been carefully studied in soft tissue. We investigated the accuracy of CTAC on PET bone images by comparing the attenuation coefficients with PET transmission scans. For this, we imaged frozen bovine femur segments in a 20x20 cm cylindrical phantom. Different regions of the bones in both images were segmented by using thresholding and erosion methods to get equivalent volume masks. Differences in linear attenuation coefficients between the two images were then calculated. We repeated this analysis using patient images from the same patient imaged on the GE Advance PET scanner and the GE Discovery STE PET/CT scanner. The impact of the errors in the linear attenuation coefficients on PET SUV measurements was evaluated by simulations using the patent images with known bone disease and elevated levels of FDG uptake in bone (e.g. SUV = 5) at disease sites. The impact of the errors in the linear attenuation coefficients was then estimated by forward projection and reconstruction, after including the effects of attenuation and attenuation correction.This work was supported in kart by Agencia Antidroga de la Comunidad de Madrid (S-SAL2007), Ministerio de Sanidad y Consumo (CIBER CB06/01/0079), and Ministerio de Industria (Programa CENIT). It was also supported in part by NIH grants R01- CA124573 and R01-CA115870

THE ROLES OF ORTHOPAEDIC PATHOLOGY AND GENETIC DETERMINANTS IN EQUINE CERVICAL STENOTIC MYELOPATHY

Cervical stenotic myelopathy (CSM) is an important musculoskeletal and neurologic disease of the horse. Clinical disease occurs due to malformations of the vertebrae in the neck causing stenosis of the cervical vertebral canal and subsequent spinal cord compression. The disease is multifactorial in nature, therefore a clearer understanding of the etiology and pathogenesis of CSM will allow for improved management and therapeutic practices. This thesis examines issues of equine CSM diagnosis, skeletal tissue pathology, and inherited genetic determinants utilizing advances in biomedical imaging technologies and equine genomics. Magnetic resonance imaging (MRI) data provided a more complete assessment of the cervical column through image acquisition in multiple planes. First, MRI was compared to standing cervical radiographs for detection of stenosis. Using canal area or the cord canal area ratio, MRI more accurately predicted sites of compression in CSM cases. Secondly, articular process skeletal pathology localized on MRI was found to be more frequent and severe in CSM horses compared to controls. In addition, lesions were generalized throughout the cervical column and not limited to the spinal cord compression sites. A subset of lesions identified on MRI was evaluated using micro-CT and histopathology. Osteochondrosis, osseous cyst-like structures, fibrous tissue replacement of bone, and osteosclerosis were observed. These lesions support likely developmental aberrations of vertebral bone and cartilage maturation with secondary biomechanical influences. Bone cyst-like structures are a novel finding in this disease. Finally, the long-standing question of the contribution of genetic determinants to CSM was investigated using a genome wide association study (GWAS). Multiple significant loci were identified supporting the influence of a complex genetic trait in clinical disease. A simple Mendelian trait controlled by one gene is unlikely given the detection of variants across multiple chromosomes. Major contributions from this research include documentation of articular process bone and cartilage pathology in horses with CSM, support for abnormal cervical vertebrae development being an important contributing factor in the etiology and/or pathogenesis of equine CSM, and evidence that multiple genetic loci contribute to the CSM disease phenotype