Accuracy of computer-aided image analysis in the diagnosis of odontogenic cysts:a systematic review

This study aimed to search for scientific evidence concerning the accuracy of computer-assisted analysis for diagnosing odontogenic cysts. A systematic review was conducted according to the PRISMA statements and considering eleven databases, including the grey literature. Protocol was registered in PROSPERO (CRD 42020189349). The PECO strategy was used to define the eligibility criteria and only studies involving diagnostic accuracy were included. Their risk of bias was investigated using the Joanna Briggs Institute Critical Appraisal tool. Out of 437 identified citations, five papers, published between 2006 and 2019, fulfilled the criteria and were included in this systematic review. A total of 5,264 images from 508 lesions, classified as radicular cyst, odontogenic keratocyst, lateral periodontal cyst, glandular odontogenic cyst, or dentigerous cyst, were analyzed. All selected articles scored low risk of bias. In three studies, the best performances were achieved when the two subtypes of odontogenic keratocysts (solitary or syndromic) were pooled together, the case-wise analysis showing a success rate of 100% for odontogenic keratocysts and radicular cysts, in one of them. In two studies, the dentigerous cyst was associated with the majority of misclassifications, and its omission from the dataset improved significantly the classification rates. The overall evaluation showed all studies presented high accuracy rates of computer-aided systems in classifying odontogenic cysts in digital images of histological tissue sections. However, due to the heterogeneity of the studies, a meta-analysis evaluating the outcomes of interest was not performed and a pragmatic recommendation about their use is not possible

A 3D environment for surgical planning and simulation

The use of Computed Tomography (CT) images and their three-dimensional (3D) reconstruction has spread in the last decade for implantology and surgery. A common use of acquired CT datasets is to be handled by dedicated software that provide a work context to accomplish preoperative planning upon. These software are able to exploit image processing techniques and computer graphics to provide fundamental information needed to work in safety, in order to minimize the surgeon possible error during the surgical operation. However, most of them carry on lacks and flaws, that compromise the precision and additional safety that their use should provide. The research accomplished during my PhD career has concerned the development of an optimized software for surgical preoperative planning. With this purpose, the state of the art has been analyzed, and main deficiencies have been identified. Then, in order to produce practical solutions, those lacks and defects have been contextualized in a medical field in particular: it has been opted for oral implantology, due to the available support of a pool of implantologists. It has emerged that most software systems for oral implantology, that are based on a multi-view approach, often accompanied with a 3D rendered model, are affected by the following problems: unreliability of measurements computed upon misleading views (panoramic one), as well as a not optimized use of the 3D environment, significant planning errors implied by the software work context (incorrect cross-sectional planes), and absence of automatic recognition of fundamental anatomies (as the mandibular canal). Thus, it has been defined a fully 3D approach, and a planning software system in particular, where image processing and computer graphic techniques have been used to create a smooth and user-friendly completely-3D environment to work upon for oral implant planning and simulation. Interpolation of the axial slices is used to produce a continuous radiographic volume and to get an isotropic voxel, in order to achieve a correct work context. Freedom of choosing, arbitrarily, during the planning phase, the best cross-sectional plane for achieving correct measurements is obtained through interpolation and texture generation. Correct orientation of the planned implants is also easily computed, by exploiting a radiological mask with radio-opaque markers, worn by the patient during the CT scan, and reconstructing the cross-sectional images along the preferred directions. The mandibular canal is automatically recognised through an adaptive surface-extracting statistical-segmentation based algorithm developed on purpose. Then, aiming at completing the overall approach, interfacing between the software and an anthropomorphic robot, in order to being able to transfer the planning on a surgical guide, has been achieved through proper coordinates change and exploiting a physical reference frame in the radiological stent. Finally, every software feature has been evaluated and validated, statistically or clinically, and it has resulted that the precision achieved outperforms the one in literature

Study and Development of Techniques for 3D Dental Identification

Ph.DDOCTOR OF PHILOSOPH

Assessment of plastics in the National Trust: a case study at Mr Straw's House

The National Trust is a charity that cares for over 300 publically accessible historic buildings and their contents across England, Wales and Northern Ireland. There have been few previous studies on preservation of plastics within National Trust collections, which form a significant part of the more modern collections of objects. This paper describes the design of an assessment system which was successfully trialled at Mr Straws House, a National Trust property in Worksop, UK. This system can now be used for future plastic surveys at other National Trust properties. In addition, the survey gave valuable information about the state of the collection, demonstrating that the plastics that are deteriorating are those that are known to be vulnerable, namely cellulose nitrate/acetate, PVC and rubber. Verifying this knowledge of the most vulnerable plastics enables us to recommend to properties across National Trust that these types should be seen as a priority for correct storage and in-depth recording

Robust computational intelligence techniques for visual information processing

The third part is exclusively dedicated to the super-resolution of Magnetic Resonance Images. In one of these works, an algorithm based on the random shifting technique is developed. Besides, we studied noise removal and resolution enhancement simultaneously. To end, the cost function of deep networks has been modified by different combinations of norms in order to improve their training. Finally, the general conclusions of the research are presented and discussed, as well as the possible future research lines that are able to make use of the results obtained in this Ph.D. thesis.This Ph.D. thesis is about image processing by computational intelligence techniques. Firstly, a general overview of this book is carried out, where the motivation, the hypothesis, the objectives, and the methodology employed are described. The use and analysis of different mathematical norms will be our goal. After that, state of the art focused on the applications of the image processing proposals is presented. In addition, the fundamentals of the image modalities, with particular attention to magnetic resonance, and the learning techniques used in this research, mainly based on neural networks, are summarized. To end up, the mathematical framework on which this work is based on, ₚ-norms, is defined. Three different parts associated with image processing techniques follow. The first non-introductory part of this book collects the developments which are about image segmentation. Two of them are applications for video surveillance tasks and try to model the background of a scenario using a specific camera. The other work is centered on the medical field, where the goal of segmenting diabetic wounds of a very heterogeneous dataset is addressed. The second part is focused on the optimization and implementation of new models for curve and surface fitting in two and three dimensions, respectively. The first work presents a parabola fitting algorithm based on the measurement of the distances of the interior and exterior points to the focus and the directrix. The second work changes to an ellipse shape, and it ensembles the information of multiple fitting methods. Last, the ellipsoid problem is addressed in a similar way to the parabola

Freehand three dimensional ultrasound for imaging components of the musculoskeletal system

There have been reports on the use of Ultrasound (US) for monitoring fracture repair and for measuring muscle volume. Change in muscle mass is a useful bio-marker for monitoring the use and disuse of muscle, and the affects of age, disease and injury. The main modality for imaging bone is X-ray and for muscle volume Magnetic Resonance (MR). Previous studies have shown US to have advantages over X-ray and MR. US can image all stages of the fracture repair process and can detect signs of healing 4-6 weeks before X-ray allowing earlier detection of possible complications. Compared to MR, US is less resource intensive, easier to access and also has fewer exclusion criteria for patients. Despite these advantages, the limited field of view that US can provide results in high operator dependency for scan interpretation and also for length and volume measurements. Three-dimensional Ultrasound (3D US) has been developed to overcome these limitations and has been used to provide extended field of view images of the foetus and the heart and to obtain accurate volume measurements for organs. In this thesis it is hypothesized that 3D US can provide a more comprehensive method of imaging fracture repair than X-ray and is also a viable alternative to MR for determining muscle volumes in vivo. Initially, an electromagnetically (EM) tracked 3D US system was evaluated for clinical use using phantom-based experiments. It was found that the presence of metal objects in or near the EM field caused distortion and resulted in errors in the volume measurements of phantoms of up to ±20%. An optically tracked system was also evaluated and it was found that length measurements of a phantom could be made to within ±1.3%. Fracture repair was monitored in five patients with lower limb fractures. Signs of healing were visible earlier on 3D US with a notable, although variable, lag between callus development on X-ray compared to 3D US. 3D US provided a clearer view of callus formation and the changes in density of the callus as it matured. Additional information gained by applying image processing methods to the 3D US data was used to develop a measure of callus density and to identify the frequency dependent appearance of the callus. Volume measurements of the rectus femoris quadricep muscle were obtained using 3DUS from eleven healthy volunteers and were validated against volume measurements derived using MR. The mean difference between muscle volume measurements obtained using 3D US and MR was 0.53 cm3 with a standard deviation of 1.09 cm3 and 95% confidence intervals of 0.20 - 1.27 cm3 In conclusion, 3D US demonstrates great potential as a tool for imaging components of the musculoskeletal system and as means of measuring callus density

Advanced Image Acquisition, Processing Techniques and Applications

"Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution

The 1993/1994 NASA Graduate Student Researchers Program

The NASA Graduate Student Researchers Program (GSRP) attempts to reach a culturally diverse group of promising U.S. graduate students whose research interests are compatible with NASA's programs in space science and aerospace technology. Each year we select approximately 100 new awardees based on competitive evaluation of their academic qualifications, their proposed research plan and/or plan of study, and their planned utilization of NASA research facilities. Fellowships of up to $22,000 are awarded for one year and are renewable, based on satisfactory progress, for a total of three years. Approximately 300 graduate students are, thus, supported by this program at any one time. Students may apply any time during their graduate career or prior to receiving their baccalaureate degree. An applicant must be sponsored by his/her graduate department chair or faculty advisor; this book discusses the GSRP in great detail