Pre-Treatment Deep Curettage Can Significantly Reduce Tumour Thickness in Thick Basal Cell Carcinoma While Maintaining a Favourable Cosmetic Outcome When Used in Combination with Topical Photodynamic Therapy

Topical photodynamic therapy (PDT) has limitations in the treatment of thick skin tumours. The aim of the study was to evaluate the effect of pre-PDT deep curettage on tumour thickness in thick (≥2 mm) basal cell carcinoma (BCC). Additionally, 3-month treatment outcome and change of tumour thickness from diagnosis to treatment were investigated. At diagnosis, mean tumour thickness was 2.3 mm (range 2.0–4.0). Pre- and post-curettage biopsies were taken from each tumour prior to PDT. Of 32 verified BCCs, tumour thickness was reduced by 50% after deep curettage (P ≤ 0.001). Mean tumour thickness was also reduced from diagnosis to treatment. At 3-month followup, complete tumour response was found in 93% and the cosmetic outcome was rated excellent or good in 100% of cases. In conclusion, deep curettage significantly reduces BCC thickness and may with topical PDT provide a favourable clinical and cosmetic short-term outcome

Joint High-Resolution Fundamental Frequency and Order Estimation

In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the MUltiple SIgnal Classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties

Multi-Pitch Estimation Exploiting Block Sparsity

We study the problem of estimating the fundamental frequencies of a signal containing multiple harmonically related sinusoidal components using a novel block sparse signal representation. An efficient algorithm for solving the resulting optimization problem is devised exploiting a novel variable step-size alternating direction method of multipliers (ADMM). The resulting algorithm has guaranteed convergence and shows notable robustness to the f 0 vs f0/2f0/2 ambiguity problem. The superiority of the proposed method, as compared to earlier presented estimation techniques, is demonstrated using both simulated and measured audio signals, clearly indicating the preferable performance of the proposed technique