Localización de contornos con precisión sub-pixel en imágenes bidimensionales y tridimensionales

Programa de Doctorado en Percepción Artificial y Aplicaciones

Muscular and pulmonary O2 uptake kinetics during moderate- and high-intensity sub-maximal knee-extensor exercise in humans

[EN] The purpose of this investigation was to determine the contribution of muscle O(2) consumption (mVO2) to pulmonary O(2) uptake (pVO2) during both low-intensity (LI) and high-intensity (HI) knee-extension exercise, and during subsequent recovery, in humans. Seven healthy male subjects (age 20-25 years) completed a series of LI and HI square-wave exercise tests in which mVO2 (direct Fick technique) and pVO2 (indirect calorimetry) were measured simultaneously. The mean blood transit time from the muscle capillaries to the lung (MTTc-l) was also estimated (based on measured blood transit times from femoral artery to vein and vein to artery). The kinetics of mVO2 and pVO2 were modelled using non-linear regression. The time constant (tau) describing the phase II pVO2 kinetics following the onset of exercise was not significantly different from the mean response time (initial time delay + tau) for mVO2 kinetics for LI (30 +/- 3 vs 30 +/- 3 s) but was slightly higher (P < 0.05) for HI (32 +/- 3 vs 29 +/- 4 s); the responses were closely correlated (r = 0.95 and r = 0.95; P < 0.01) for both intensities. In recovery, agreement between the responses was more limited both for LI (36 +/- 4 vs 18 +/- 4 s, P < 0.05; r = -0.01) and HI (33 +/- 3 vs 27 +/- 3 s, P > 0.05; r = -0.40). MTTc-l was approximately 17 s just before exercise and decreased to 12 and 10 s after 5 s of exercise for LI and HI, respectively. These data indicate that the phase II pVO2 kinetics reflect mVO2 kinetics during exercise but not during recovery where caution in data interpretation is advised. Increased mVO2 probably makes a small contribution to during the first 15-20 s of exercise.

Localización de contornos con precisión sub-píxel en imágenes bidimensionales y tridimensionales

[ES] La detección de contornos en una imagen es un proceso fundamental para poder realizar posteriores cálculos sobre ella. Cuando la precisión es importante, se necesitan desarrollar métodos más exactos. Un objetivo de la informática aplicada al campo de la imagen médica consiste en aportar la mayor información posible al médico para ayudarle en su diagnóstico. Así por ejemplo, si consideramos una angiografía, que no es más que la fotografía de una zona de vasos sanguíneos usando rayos X, podemos observar que la detección precisa de los contornos o bordes de los vasos es un paso previo fundamental para poder estimar medidas concretas sobre la vasculatura, como por ejemplo el grosor o la curvatura de los vasos en cada píxel, lo cual permitiría dar al médico un diagnóstico más preciso.