A deep learning framework for quality assessment and restoration in video endoscopy

Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, specular reflections, floating objects and pixel saturation impede the visual interpretation and the automated analysis of endoscopy videos. Given the widespread use of endoscopy in different clinical applications, we contend that the robust and reliable identification of such artifacts and the automated restoration of corrupted video frames is a fundamental medical imaging problem. Existing state-of-the-art methods only deal with the detection and restoration of selected artifacts. However, typically endoscopy videos contain numerous artifacts which motivates to establish a comprehensive solution. We propose a fully automatic framework that can: 1) detect and classify six different primary artifacts, 2) provide a quality score for each frame and 3) restore mildly corrupted frames. To detect different artifacts our framework exploits fast multi-scale, single stage convolutional neural network detector. We introduce a quality metric to assess frame quality and predict image restoration success. Generative adversarial networks with carefully chosen regularization are finally used to restore corrupted frames. Our detector yields the highest mean average precision (mAP at 5% threshold) of 49.0 and the lowest computational time of 88 ms allowing for accurate real-time processing. Our restoration models for blind deblurring, saturation correction and inpainting demonstrate significant improvements over previous methods. On a set of 10 test videos we show that our approach preserves an average of 68.7% which is 25% more frames than that retained from the raw videos.Comment: 14 page

HETDEX pilot survey for emission-line galaxies - I. Survey design, performance, and catalog

We present a catalog of emission-line galaxies selected solely by their emission-line fluxes using a wide-field integral field spectrograph. This work is partially motivated as a pilot survey for the upcoming Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). We describe the observations, reductions, detections, redshift classifications, line fluxes, and counterpart information for 397 emission-line galaxies detected over 169 sq.arcmin with a 3500-5800 Ang. bandpass under 5 Ang. full-width-half-maximum (FWHM) spectral resolution. The survey's best sensitivity for unresolved objects under photometric conditions is between 4-20 E-17 erg/s/sq.cm depending on the wavelength, and Ly-alpha luminosities between 3-6 E42 erg/s are detectable. This survey method complements narrowband and color-selection techniques in the search for high redshift galaxies with its different selection properties and large volume probed. The four survey fields within the COSMOS, GOODS-N, MUNICS, and XMM-LSS areas are rich with existing, complementary data. We find 104 galaxies via their high redshift Ly-alpha emission at 1.9<z<3.8, and the majority of the remainder objects are low redshift [OII]3727 emitters at z<0.56. The classification between low and high redshift objects depends on rest frame equivalent width, as well as other indicators, where available. Based on matches to X-ray catalogs, the active galactic nuclei (AGN) fraction amongst the Ly-alpha emitters (LAEs) is 6%. We also analyze the survey's completeness and contamination properties through simulations. We find five high-z, highly-significant, resolved objects with full-width-half-maximum sizes >44 sq.arcsec which appear to be extended Ly-alpha nebulae. We also find three high-z objects with rest frame Ly-alpha equivalent widths above the level believed to be achievable with normal star formation, EW(rest)>240 Ang.Comment: 45 pages, 36 figures, 5 tables, submitted to ApJ

PACS Evolutionary Probe (PEP) - A Herschel Key Program

Deep far-infrared photometric surveys studying galaxy evolution and the nature of the cosmic infrared background are a key strength of the Herschel mission. We describe the scientific motivation for the PACS Evolutionary Probe (PEP) guaranteed time key program and its role in the complement of Herschel surveys, and the field selection which includes popular multiwavelength fields such as GOODS, COSMOS, Lockman Hole, ECDFS, EGS. We provide an account of the observing strategies and data reduction methods used. An overview of first science results illustrates the potential of PEP in providing calorimetric star formation rates for high redshift galaxy populations, thus testing and superseeding previous extrapolations from other wavelengths, and enabling a wide range of galaxy evolution studies.Comment: 13 pages, 12 figures, accepted for publication in A&

A review of RFI mitigation techniques in microwave radiometry

Radio frequency interference (RFI) is a well-known problem in microwave radiometry (MWR). Any undesired signal overlapping the MWR protected frequency bands introduces a bias in the measurements, which can corrupt the retrieved geophysical parameters. This paper presents a literature review of RFI detection and mitigation techniques for microwave radiometry from space. The reviewed techniques are divided between real aperture and aperture synthesis. A discussion and assessment of the application of RFI mitigation techniques is presented for each type of radiometer.Peer ReviewedPostprint (published version