Lossless Medical Image Compression by Using Difference Transform.

This paper introduces a new method of compressing digital images by using the Difference Transform applied in medical imaging. The Difference Transform algorithm performs the decorrelation process of image data, and in this way improves the encoding process, achieving a file with a smaller size than the original. The proposed method proves to be competitive and in many cases better than the standards used for medical images such as TIFF or PNG. In addition, the Difference Transform can replace other transforms like Cosine or Wavelet.

Territorial Strategy of Medical Units for Addressing the First Wave of the COVID-19 Pandemic in the Metropolitan Area of Mexico City: Analysis of Mobility, Accessibility and Marginalization.

BACKGROUND: The COVID-19 pandemic has caused an exponential increase in the demand for medical care worldwide. In Mexico, the COVID Medical Units (CMUs) conversion strategy was implemented. OBJECTIVE: To evaluate the CMU coverage strategy in the Mexico City Metropolitan Area (MCMA) by territory. MATERIALS: The CMU directory was used, as were COVID-19 infection and mobility statistics and Mexican 2020 census information at the urban geographic area scale. The degree of urban marginalization by geographic area was also considered. METHOD: Using descriptive statistics and the calculation of a CMU accessibility index, population aggregates were counted based on coverage radii. In addition, two regression models are proposed to explain (1) the territorial and temporal trend of COVID-19 infections in the MCMA and (2) the mobility of the COVID-infected population visiting medical units. RESULTS: The findings of the evaluation of the CMU strategy were (1) in the MCMA, COVID-19 followed a pattern of contagion from the urban center to the periphery; (2) given the growth in the number of cases and the overload of medical units, the population traveled greater distances to seek medical care; (3) after the CMU strategy was evaluated at the territory level, it was found that 9 out of 10 inhabitants had a CMU located approximately 7 km away; and (4) at the metropolitan level, the lowest level of accessibility to the CMU was recorded for the population with the highest levels of marginalization, i.e., those residing in the urban periphery.