Biomedical optics express

Many people suffer from different skin diseases, which can be diverse and varied. Most skin diseases cause disorders in the skin, such as changes in color, texture, and appearance manifesting in spots, swelling, scaling, ulcers, etc. One of the diseases that represents a serious health problem is skin cancer. The most dangerous skin cancer is malignant melanoma, which can cause death if not detected early. Therefore, development of new and accurate diagnosis methodologies to increase the chance of early detection is important. In this work, an analysis to discriminate between malignant melanoma and three types of benign skin lesions–melanocytic nevus, dermatofibroma, and seborrheic keratosis–is realized by calculating spectral indexes based on the real and imaginary parts of a fractional nonlinear filter obtained by affecting the modulus of the fractional Fourier transform by an exponent k. The fractional spectral indexes were calculated by working with selected sub-images obtained by dividing the input image. Also, a variation was implemented when the Hermite transform is used to calculate the fractional nonlinear filter. Discrimination between malignant melanoma and benign skin lesions was achieved with a 99.7% confidence level.Biomedical Optics Expresshttps://www.osapublishing.org/boe/abstract.cfm?uri=boe-10-12-604

Automatic identification of diatoms using descriptors obtained in the plane of frequencies

ScopusDiatoms are unicellular algae that have as characteristic to be composed mainly of silice. Currently, its study has become relevant due to its multiple applications that include forensic medicine, palaeoenvironmental reconstructions and its use as biological bioindicators of water quality. It is estimated that there are around 100,000 different diatom species, showing a high similarity between some of them. For these reasons, their identification is slow and often unreliable. Additionally, the number of specialists capable of carrying out an identification is not sufficient in comparison to the number of samples that usually have to be analyzed. It is for these reasons that there is a need to have automated systems that perform this task. In the present work, an automatic identification system was created for 46 diatom species with different morphology using images obtained with optical microscopy. This system was designed by calculating descriptors in the plane of frequencies using three different methodologies: the Fourier Mellin transform, the concentric ring binary masks and the fractional Fourier transform. The methods used for the identification system has as main characteristics to be robust to changes of scale, rotations, translations, and lighting. Additionally, the number of images used as reference images compared to other techniques found in the literature is lower, which gives a higher possibility that it can be extended to other species.doi: 10.1117/12.232086