Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma
is life threating when it grows beyond the dermis of the skin. Hence, depth is
an important factor to diagnose melanoma. This paper introduces a non-invasive
computerized dermoscopy system that considers the estimated depth of skin
lesions for diagnosis. A 3-D skin lesion reconstruction technique using the
estimated depth obtained from regular dermoscopic images is presented. On basis
of the 3-D reconstruction, depth and 3-D shape features are extracted. In
addition to 3-D features, regular color, texture, and 2-D shape features are
also extracted. Feature extraction is critical to achieve accurate results.
Apart from melanoma, in-situ melanoma the proposed system is
designed to diagnose basal cell carcinoma, blue nevus, dermatofibroma,
haemangioma, seborrhoeic keratosis, and normal mole lesions. For experimental
evaluations, the PH2, ISIC: Melanoma Project, and ATLAS dermoscopy data sets is
considered. Different feature set combinations is considered and performance is
evaluated. Significant performance improvement is reported the post inclusion of
estimated depth and 3-D features. The good classification scores of sensitivity
= 96%, specificity = 97% on PH2 data set and
sensitivity = 98%, specificity = 99% on the ATLAS
data set is achieved. Experiments conducted to estimate tumor depth from 3-D
lesion reconstruction is presented. Experimental results achieved prove that the
proposed computerized dermoscopy system is efficient and can be used to diagnose
varied skin lesion dermoscopy images.
Geometric spanners can be used for efficient routing in wireless ad hoc networks. Computation of existing spanners for ad hoc networks primarily focused on geometric properties without considering network requirements. In this paper, we propose a new spanner called constrained Delaunay triangulation (CDT) which considers both geometric properties and network requirements. The CDT is formed by introducing a small set of constraint edges into local Delaunay triangulation (LDel) to reduce the number of hops between nodes in the network graph. We have simulated the CDT using network simulator (ns-2.28) and compared with Gabriel graph (GG), relative neighborhood graph (RNG), local Delaunay triangulation (LDel), and planarized local Delaunay triangulation (PLDel). The simulation results show that the minimum number of hops from source to destination is less than other spanners. We also observed the decrease in delay, jitter, and improvement in throughput.
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