Texture and Colour in Image Analysis

Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

OBJECTIVE IMAGING TECHNIQUE FOR PSORIASIS ANALYSIS

Most of skin assessment methods applied in clinical practice use visual and tactile senses of dermatologists to assess features and conditions of skin diseases. However, the assessment can be subjective resulting in intra- and inter-rater variability. This research investigates the objective skin roughness measurement for psoriasis lesion assessment

OBJECTIVE IMAGING TECHNIQUE FOR PSORIASIS ANALYSIS

Most of skin assessment methods applied in clinical practice use visual and tactile senses of dermatologists to assess features and conditions of skin diseases. However, the assessment can be subjective resulting in intra- and inter-rater variability. This research investigates the objective skin roughness measurement for psoriasis lesion assessment

Present and Future of Surface-Enhanced Raman Scattering.

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article

Depth data improves non-melanoma skin lesion segmentation and diagnosis

Examining surface shape appearance by touching and observing a lesion from different points of view is a part of the clinical process for skin lesion diagnosis. Motivated by this, we hypothesise that surface shape embodies important information that serves to represent lesion identity and status. A new sensor, Dense Stereo Imaging System (DSIS) allows us to capture 1:1 aligned 3D surface data and 2D colour images simultaneously. This thesis investigates whether the extra surface shape appearance information, represented by features derived from the captured 3D data benefits skin lesion analysis, particularly on the tasks of segmentation and classification. In order to validate the contribution of 3D data to lesion identification, we compare the segmentations resulting from various combinations of images cues (e.g., colour, depth and texture) embedded in a region-based level set segmentation method. The experiments indicate that depth is complementary to colour. Adding the 3D information reduces the error rate from 7:8% to 6:6%. For the purpose of evaluating the segmentation results, we propose a novel ground truth estimation approach that incorporates a prior pattern analysis of a set of manual segmentations. The experiments on both synthetic and real data show that this method performs favourably compared to the state of the art approach STAPLE [1] on ground truth estimation. Finally, we explore the usefulness of 3D information to non-melanoma lesion diagnosis by tests on both human and computer based classifications of five lesion types. The results provide evidence for the benefit of the additional 3D information, i.e., adding the 3D-based features gives a significantly improved classification rate of 80:7% compared to only using colour features (75:3%). The three main contributions of the thesis are improved methods for lesion segmentation, non-melanoma lesion classification and lesion boundary ground-truth estimation

IMAGING FOR SKIN ROUGHNESS ANALYSIS

Kcbanyakan kaedah penilaian kulit digunakan dalam amalan klinikal menggunakan deria visual dan sentuhan pakar dermatologi untuk menilai ciri-ciri dan syarat-syarat penyakit kulit. Walau bagaimanapun, penilaian bersifat subjektif dan menyebabkan perbezaan basil penilaian antara penilai. Kajian ini menyiasat masalah ukuran kekasaran kulit untuk penilaian luka psoriasis. Psoriasis adalab penyakit kulit yang tidak boleh diubati. menjejaskan 2-3% penduduk dunia. Psoriasis scaliness adalah parameter penilaian utama daripada Psoriasis Area and Severity Index (PAS!) yang bersifat subjektif. PAS! scqliness menentukan jumlah sisik pada permukaan luka. Kajian ini mencadangkan penggabungan algoritma 3D surface roughness dan teknik clustering untuk menentuka':l markah PAS! scaliness secara objektif

Membrane vesicles: Examination of biophysical properties with atomic force microscopy

Extracellular vesicles (EVs) are not only intensively studied to increase our fundamental knowledge on their functioning, but also for diagnosis, therapeutics and drug delivery purposes. To improve the current and potential applications of EVs, a fundamental understanding of their stability, structure, and function is crucial. Such studies can be conducted at the single particle level to gain biological and physical information about the vesicles and the particle to particle variability. A suitable technique to investigate EVs under near- to physiological conditions is atomic force microscopy (AFM). Operated in liquid, it provides images of the EVs while mechanical properties of the particles can be obtained as well. Here we present our approach and the latest results in studying the structure and mechanics of these particles

Qualifying 4D Deforming Surfaces by Registered Differential Features

Institute of Perception, Action and BehaviourRecent advances in 4D data acquisition systems in the field of Computer Vision have opened up many exciting new possibilities for the interpretation of complex moving surfaces. However, a fundamental problem is that this has also led to a huge increase in the volume of data to be handled. Attempting to make sense of this wealth of information is then a core issue to be addressed if such data can be applied to more complex tasks. Similar problems have been historically encountered in the analysis of 3D static surfaces, leading to the extraction of higher-level features based on analysis of the differential geometry.Our central hypothesis is that there exists a compact set of similarly useful descriptors for the analysis of dynamic 4D surfaces. The primary advantages in considering localised changes are that they provide a naturally useful set of invariant characteristics. We seek a constrained set of terms - a vocabulary - for describing all types of deformation. By using this, we show how to describe what the surface is doing more effectively; and thereby enable better characterisation, and consequently more effective visualisation and comparison.This thesis investigates this claim. We adopt a bottom-up approach of the problem, in which we acquire raw data from a newly constructed commercial 4D data capture system developed by our industrial partners. A crucial first step resolves the temporal non-linear registration between instances of the captured surface. We employ a combined optical/range flow to guide a conformation over a sequence. By extending the use of aligned colour information alongside the depth data we improve this estimation in the case of local surface motion ambiguities. By employing a KLT/thin-plate-spline method we also seek to preserve global deformation for regions with no estimate.We then extend aspects of differential geometry theory for existing static surface analysis to the temporal domain. Our initial formulation considers the possible intrinsic transitions from the set of shapes defined by the variations in the magnitudes of the principal curvatures. This gives rise to a total of 15 basic types of deformation. The change in the combined magnitudes also gives an indication of the extent of change. We then extend this to surface characteristics associated with expanding, rotating and shearing; to derive a full set of differential features.Our experimental results include qualitative assessment of deformations for short episodic registered sequences of both synthetic and real data. The higher-level distinctions extracted are furthermore a useful first step for parsimonious feature extraction, which we then proceed to demonstrate can be used as a basis for further analysis. We ultimately evaluate this approach by considering shape transition features occurring within the human face, and the applicability for identification and expression analysis tasks