Segmentation and Classification of Skin Lesions for Disease Diagnosis

In this paper, a novel approach for automatic segmentation and classification of skin lesions is proposed. Initially, skin images are filtered to remove unwanted hairs and noise and then the segmentation process is carried out to extract lesion areas. For segmentation, a region growing method is applied by automatic initialization of seed points. The segmentation performance is measured with different well known measures and the results are appreciable. Subsequently, the extracted lesion areas are represented by color and texture features. SVM and k-NN classifiers are used along with their fusion for the classification using the extracted features. The performance of the system is tested on our own dataset of 726 samples from 141 images consisting of 5 different classes of diseases. The results are very promising with 46.71% and 34% of F-measure using SVM and k-NN classifier respectively and with 61% of F-measure for fusion of SVM and k-NN.Comment: 10 pages, 6 figures, 2 Tables in Elsevier, Proceedia Computer Science, International Conference on Advanced Computing Technologies and Applications (ICACTA-2015

A survey, review, and future trends of skin lesion segmentation and classification

The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion analysis is an emerging field of research that has the potential to alleviate the burden and cost of skin cancer screening. Researchers have recently indicated increasing interest in developing such CAD systems, with the intention of providing a user-friendly tool to dermatologists to reduce the challenges encountered or associated with manual inspection. This article aims to provide a comprehensive literature survey and review of a total of 594 publications (356 for skin lesion segmentation and 238 for skin lesion classification) published between 2011 and 2022. These articles are analyzed and summarized in a number of different ways to contribute vital information regarding the methods for the development of CAD systems. These ways include: relevant and essential definitions and theories, input data (dataset utilization, preprocessing, augmentations, and fixing imbalance problems), method configuration (techniques, architectures, module frameworks, and losses), training tactics (hyperparameter settings), and evaluation criteria. We intend to investigate a variety of performance-enhancing approaches, including ensemble and post-processing. We also discuss these dimensions to reveal their current trends based on utilization frequencies. In addition, we highlight the primary difficulties associated with evaluating skin lesion segmentation and classification systems using minimal datasets, as well as the potential solutions to these difficulties. Findings, recommendations, and trends are disclosed to inform future research on developing an automated and robust CAD system for skin lesion analysis

Medical image synthesis using generative adversarial networks: towards photo-realistic image synthesis

This proposed work addresses the photo-realism for synthetic images. We introduced a modified generative adversarial network: StencilGAN. It is a perceptually-aware generative adversarial network that synthesizes images based on overlaid labelled masks. This technique can be a prominent solution for the scarcity of the resources in the healthcare sector

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

Immunocytochemical investigation of caries-induced neural, vascular and leucocyte responses in human primary and permanent tooth pulp.

This immunocytochemical study investigated nerve density and morphology, neuropeptide expression, vascular status and leucocyte accumulation within the human tooth pulp. It specifically examined differences between the primary and permanent dentition, and explored the effect of caries on the above parameters. The study also sought to correlate quantitative findings with a reported pain history. Mandibular first permanent molars and second primary molars were obtained from children requiring dental extractions under general anaesthesia. A simple pain history was elicited for each patient. Following exodontia, teeth were split longitudinally, placed in fixative and were categorised as intact, moderately carious or grossly carious. The coronal pulps were removed and serial frozen sections were processed for indirect immunofluorescence. Triple-labelling regimes were employed using combinations of the following antisera: i) protein gene product 9.5 (a general neuronal marker; ii) the neuropeptides calcitonin gene-related peptide, substance P, vasoactive intestinal polypeptide or neuropeptide Y; iii) Ulex europeaus I lectin (a label for vascular endothelium) and iv) leucocyte common antigen (a general leucocyte marker). Image analysis was then used to determine the percentage area of immunostaining for each label within different anatomical regions of the coronal pulp. The findings revealed that there were significant inter-dentition differences for the biological variables under investigation. Essentially, in intact samples, innervation density and neuropeptide expression were greater in permanent teeth but primary tooth pulps were more vascular and contained a greater number of leucocytes. With caries progression, both dentitions demonstrated significant increases in neural density, neuropeptide expression and leucocyte accumulation. However, changes in pulpal vascularity were limited to the pulp hom regions. The only factors found to correlate with the reported pain history were substance P and vasoactive intestinal polypeptide expression. These peptides were significantly upregulated in painful pulpitis. Finally, there was evidence to suggest that changes in neuropeptide expression were associated with changes in vascular status and leucocyte accumulation within the inflamed pulp. In conclusion, this study has established that significant inter-dentition differences exist in pulpal biology. Furthermore, dynamic changes in pulpal neural density and neuropeptide expression seem to occur with caries progression. These findings are likely to have functional importance in terms of pain experience, inflammation and healing, and thus may help to direct the development of novel therapeutic strategies for the compromised dental pulp