Melanoma Recognition Using Representative and Discriminative Kernel Classifiers

Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work on this topic has focused mostly on developing ad\--hoc segmentation and feature extraction methods. In this paper we take a completely different approach. We put the emphasis on the learning part of the algorithm by using two kernel\--based classifiers, one discriminative and one probabilistic. As a discriminative approach we chose support vector machines, a state of the art large\--margin classifier which was proved very successful on visual applications. As a probabilistic approach we chose spin glass\--Markov random fields, a kernel Gibbs distribution inspired by results of statistical physics. We benchmarked these algorithms against the (to our knowledge) state\--of\--the\--art method on melanoma recognition, exploring how performance changes by using color or textural features, and how it is affected by the quality of the segmentation mask. We show with extensive experiments that the support vector machine approach outperforms the existing method and, on two classes out of three, it achieves performances comparable to those obtained by expert clinicians

Kernel Methods for Melanoma Recognition

Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work on this topic has focused mostly on developing ad-hoc segmentation and feature extraction methods. In this paper we take a completely different approach. We put the emphasis on the learning part of the algorithm by using two kernel-based classifiers, one discriminative and one probabilistic. As a discriminative approach we chose support vector machines, a state of the art large-margin classifier which was proved very successful on visual applications. As a probabilistic approach we chose spin glass-Markov random fields, a kernel Gibbs distribution inspired by results of statistical physics. We benchmarked these algorithms against the (to our knowledge) state-of-the-art method on melanoma recognition, exploring how performance changes by using color or textural features, and how it is affected by the quality of the segmentation mask. We show with extensive experiments that the support vector machine approach outperforms the existing method and, on two classes out of three, it achieves performances comparable to those obtained by expert clinician

Melanoma Recognition using Kernel Classifiers

Melanoma is the most deadly skin cancer. Early diagnosis is a current challenge for clinicians. Current algorithms for skin lesions classification focus mostly on segmentation and feature extraction. This paper instead puts the emphasis on the learning process, proposing two kernel-based classifiers: support vector machines, and spin glass-Markov random fields. We benchmarked these algorithms against a state-of-the-art method on melanoma recognition. We show with extensive experiments that the support vector machine approach outperforms the other methods, proving to be an effective classification algorithm for computer assisted diagnosis of melanoma

The STRIP instrument of the Large Scale Polarization Explorer: microwave eyes to map the Galactic polarized foregrounds

In this paper we discuss the latest developments of the STRIP instrument of the "Large Scale Polarization Explorer" (LSPE) experiment. LSPE is a novel project that combines ground-based (STRIP) and balloon-borne (SWIPE) polarization measurements of the microwave sky on large angular scales to attempt a detection of the "B-modes" of the Cosmic Microwave Background polarization. STRIP will observe approximately 25% of the Northern sky from the "Observatorio del Teide" in Tenerife, using an array of forty-nine coherent polarimeters at 43 GHz, coupled to a 1.5 m fully rotating crossed-Dragone telescope. A second frequency channel with six-elements at 95 GHz will be exploited as an atmospheric monitor. At present, most of the hardware of the STRIP instrument has been developed and tested at sub-system level. System-level characterization, starting in July 2018, will lead STRIP to be shipped and installed at the observation site within the end of the year. The on-site verification and calibration of the whole instrument will prepare STRIP for a 2-years campaign for the observation of the CMB polarization.Comment: 17 pages, 15 figures, proceedings of the SPIE Astronomical Telescopes + Instrumentation conference "Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy IX", on June 15th, 2018, Austin (TX

Heat treatment procedure of the Aluminium 6061-T651 for the Ariel Telescope mirrors

The Atmospheric Remote-Sensing Infrared Exoplanet Large Survey (Ariel) is the M4 mission adopted by ESA’s ”Cosmic Vision” program. Its launch is scheduled for 2029. The purpose of the mission is the study of exoplanetary atmospheres on a target of ∼ 1000 exoplanets. Ariel scientific payload consists of an off-axis, unobscured Cassegrain telescope. The light is directed towards a set of photometers and spectrometers with wavebands between 0.5 and 7.8 µm and operating at cryogenic temperatures. The Ariel Space Telescope consists of a primary parabolic mirror with an elliptical aperture of 1.1· 0.7 m, followed by a hyperbolic secondary, a parabolic collimating tertiary and a flat-folding mirror directing the output beam parallel to the optical bench; all in bare aluminium. The choice of bare aluminium for the realization of the mirrors is dictated by several factors: maximizing the heat exchange, reducing the costs of materials and technological advancement. To date, an aluminium mirror the size of Ariel’s primary has never been made. The greatest challenge is finding a heat treatment procedure that stabilizes the aluminium, particularly the Al6061T651 Laminated alloy. This paper describes the study and testing of the heat treatment procedure developed on aluminium samples of different sizes (from 50mm to 150mm diameter), on 0.7m diameter mirror, and discusses future steps

The detector control unit of the fine guidance sensor instrument on-board the ARIEL mission: design status

ARIEL is an ESA mission whose scientific goal is to investigate exoplanetary atmospheres. The payload is composed by two instruments: AIRS (ARIEL IR Spectrometer) and FGS (Fine Guidance System). The FGS detection chain is composed by two HgCdTe detectors and by the cold Front End Electronics (SIDECAR), kept at cryogenic temperatures, interfacing with the F-DCU (FGS Detector Control Unit) boards that we will describe thoroughly in this paper. The F-DCU are situated in the warm side of the payload in a box called FCU (FGS Control Unit) and contribute to the FGS VIS/NIR imaging and NIR spectroscopy. The F-DCU performs several tasks: drives the detectors, processes science data and housekeeping telemetries, manages the commands exchange between the FGS/DPU (Data Processing Unit) and the SIDECARs and provides high quality voltages to the detectors. This paper reports the F-DCU status, describing its architecture, the operation and the activities, past and future necessary for its development

The instrument control unit of the ARIEL payload: design evolution following the unit and payload subsystems SRR (system requirements review)

ARIEL (Atmospheric Remote-sensing InfraRed Large-survey) is a medium-class mission of the European Space Agency, part of the Cosmic Vision program, whose launch is foreseen by early 2029. ARIEL aims to study the composition of exoplanet atmospheres, their formation and evolution. The ARIEL’s target will be a sample of about 1000 planets observed with one or more of the following methods: transit, eclipse and phase-curve spectroscopy, at both visible and infrared wavelengths simultaneously. The scientific payload is composed by a reflective telescope having a 1m-class elliptical primary mirror, built in solid Aluminium, and two focal-plane instruments: FGS and AIRS. FGS (Fine Guidance System)1 has the double purpose, as suggested by its name, of performing photometry (0.50-0.55 µm) and low resolution spectrometry over three bands (from 0.8 to 1.95 µm) and, simultaneously, to provide data to the spacecraft AOCS (Attitude and Orbit Control System) with a cadence of 10 Hz and contributing to reach a 0.02 arcsec pointing accuracy for bright targets. AIRS (ARIEL InfraRed Spectrometer) instrument will perform IR spectrometry in two wavelength ranges: between 1.95 and 3.9 µm (with a spectral resolution R > 100) and between 3.9 and 7.8 µm with a spectral resolution R > 30. This paper provides the status of the ICU (Instrument Control Unit), an electronic box whose purpose is to command and supply power to AIRS (as well as acquire science data from its two channels) and to command and control the TCU (Telescope Control Unit)

Preliminary surface charging analysis of Ariel payload dielectrics in early transfer orbit and L2-relevant space environment

Ariel [1] is the M4 mission of the ESA’s Cosmic Vision Program 2015-2025, whose aim is to characterize by lowresolution transit spectroscopy the atmospheres of over one thousand warm and hot exoplanets orbiting nearby stars. The operational orbit of the spacecraft is baselined as a large amplitude halo orbit around the Sun-Earth L2 Lagrangian point, as it offers the possibility of long uninterrupted observations in a fairly stable radiative and thermo-mechanical environment. A direct escape injection with a single passage through the Earth radiation belts and no eclipses is foreseen. The space environment around Earth and L2 presents significant design challenges to all spacecraft, including the effects of interactions with Sun radiation and charged particles owning to the surrounding plasma environment, potentially leading to dielectrics charging and unwanted electrostatic discharge (ESD) phenomena endangering the Payload operations and its data integrity. Here, we present some preliminary simulations and analyses about the Ariel Payload dielectrics and semiconductors charging along the transfer orbit from launch to L2 include