473 research outputs found
Computationally efficient cardiac views projection using 3D Convolutional Neural Networks
4D Flow is an MRI sequence which allows acquisition of 3D images of the
heart. The data is typically acquired volumetrically, so it must be reformatted
to generate cardiac long axis and short axis views for diagnostic
interpretation. These views may be generated by placing 6 landmarks: the left
and right ventricle apex, and the aortic, mitral, pulmonary, and tricuspid
valves. In this paper, we propose an automatic method to localize landmarks in
order to compute the cardiac views. Our approach consists of first calculating
a bounding box that tightly crops the heart, followed by a landmark
localization step within this bounded region. Both steps are based on a 3D
extension of the recently introduced ENet. We demonstrate that the long and
short axis projections computed with our automated method are of equivalent
quality to projections created with landmarks placed by an experienced cardiac
radiologist, based on a blinded test administered to a different cardiac
radiologist
ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans
Medical images with specific pathologies are scarce, but a large amount of
data is usually required for a deep convolutional neural network (DCNN) to
achieve good accuracy. We consider the problem of segmenting the left
ventricular (LV) myocardium on late gadolinium enhancement (LGE) cardiovascular
magnetic resonance (CMR) scans of which only some of the scans have scar
tissue. We propose ScarGAN to simulate scar tissue on healthy myocardium using
chained generative adversarial networks (GAN). Our novel approach factorizes
the simulation process into 3 steps: 1) a mask generator to simulate the shape
of the scar tissue; 2) a domain-specific heuristic to produce the initial
simulated scar tissue from the simulated shape; 3) a refining generator to add
details to the simulated scar tissue. Unlike other approaches that generate
samples from scratch, we simulate scar tissue on normal scans resulting in
highly realistic samples. We show that experienced radiologists are unable to
distinguish between real and simulated scar tissue. Training a U-Net with
additional scans with scar tissue simulated by ScarGAN increases the percentage
of scar pixels correctly included in LV myocardium prediction from 75.9% to
80.5%.Comment: 12 pages, 5 figures. To appear in MICCAI DLMIA 201
SÃndrome de Burnout en personal de salud de emergencia del Hospital Central de la Fuerza Aérea del Perú. Febrero-julio 2014
El documento digital no refiere asesor.Establece el grado de presentación del sÃndrome de Burnout en el personal de salud que labora en el Servicio de Emergencia del Hospital Central de la Fuerza Aérea del Perú en el 2014. El sÃndrome de Burnout es una afección que consiste en un estrés crónico caracterizado por sÃntomas de despersonalización, cansancio emocional, abandono de la realización personal; que sufren los profesionales que tienen una atención intensa y prolongada con personas que están en situación de necesidad o dependencia. En esta situación por la naturaleza de su labor, se encuentran los médicos, enfermeras, policÃas, profesores, asistentes sociales, etc.
El personal de salud de emergencia está en contacto con personas que acuden por alguna urgencia o emergencia, estas preocupaciones son transmitidas al personal que labora en esta área y pueden desarrollar el sÃndrome de Burnout. La presentación de este sÃndrome se puede ver reflejado en la disminución del rendimiento y motivación en el trabajo, asà como un distanciamiento con los pacientes y sus familiares.Trabajo académic
Natural Adversarial Objects
Although state-of-the-art object detection methods have shown compelling
performance, models often are not robust to adversarial attacks and
out-of-distribution data. We introduce a new dataset, Natural Adversarial
Objects (NAO), to evaluate the robustness of object detection models. NAO
contains 7,934 images and 9,943 objects that are unmodified and representative
of real-world scenarios, but cause state-of-the-art detection models to
misclassify with high confidence. The mean average precision (mAP) of
EfficientDet-D7 drops 74.5% when evaluated on NAO compared to the standard
MSCOCO validation set.
Moreover, by comparing a variety of object detection architectures, we find
that better performance on MSCOCO validation set does not necessarily translate
to better performance on NAO, suggesting that robustness cannot be simply
achieved by training a more accurate model.
We further investigate why examples in NAO are difficult to detect and
classify. Experiments of shuffling image patches reveal that models are overly
sensitive to local texture. Additionally, using integrated gradients and
background replacement, we find that the detection model is reliant on pixel
information within the bounding box, and insensitive to the background context
when predicting class labels. NAO can be downloaded at
https://drive.google.com/drive/folders/15P8sOWoJku6SSEiHLEts86ORfytGezi8
Synthesis and evaluation of 18F-labeled carbonic anhydrase IX inhibitors for imaging with positron emission tomography
Two carbonic anhydrase IX (CA IX) inhibitors were radiolabeled with (18)F, and evaluated for imaging CA IX expression. Despite good affinity for CA IX and excellent plasma stability, uptake of both tracers in CA IX-expressing HT-29 tumor xenografts in mice was low. (18)F-FEC accumulated predominately in the liver and nasal cavity, whereas a significant amount of (18)F-U-104 was retained in blood. Due to minimal uptake in HT-29 tumors compared to other organs/tissues, these two tracers are not suitable for use for CA IX-targeted imaging
Uncovering Red and Dusty Ultraluminous X-Ray Sources with Spitzer
We present a mid-infrared (IR) sample study of nearby ultraluminous X-ray sources (ULXs) using multiepoch observations with the Infrared Array Camera (IRAC) on the Spitzer Space Telescope. Spitzer/IRAC observations taken after 2014 were obtained as part of the Spitzer Infrared Intensive Transients Survey. Our sample includes 96 ULXs located within 10 Mpc. Of the 96 ULXs, 12 have candidate counterparts consistent with absolute mid-IR magnitudes of supergiants, and 16 counterparts exceeded the mid-IR brightness of single supergiants and are thus more consistent with star clusters or non-ULX background active galactic nuclei. The supergiant candidate counterparts exhibit a bimodal color distribution in a Spitzer/IRAC color–magnitude diagram, where "red" and "'blue" ULXs fall in IRAC colors [3.6] – [4.5] ~ 0.7 and [3.6] – [4.5] ~ 0.0, respectively. The mid-IR colors and absolute magnitudes of four "red" and five "blue" ULXs are consistent with those of supergiant B[e] (sgB[e]) and red supergiant (RSG) stars, respectively. Although "blue," RSG-like mid-IR ULX counterparts likely host RSG mass donors; we propose that "red" counterparts are ULXs exhibiting the "B[e] phenomenon" rather than hosts of sgB[e] mass donors. We show that the mid-IR excess from the "red" ULXs is likely due to thermal emission from circumstellar or circumbinary dust. Using dust as a probe for total mass, we estimate mass-loss rates of Ṁ ~ 1 x 10^(-4) M_⊙ yr^(−1) in dust-forming outflows of red ULXs. Based on the transient mid-IR behavior and its relatively flat spectral index, α = −0.19 ± 0.1, we suggest that the mid-IR emission from Holmberg IX X-1 originates from a variable jet
Short-term results of a randomized clinical trial comparing Lichtenstein open repair with totally extraperitoneal laparoscopic inguinal hernia repair
The Recent Volcanic History of Axial Seamount: Geophysical Insights into Past Eruption Dynamics with an Eye Toward Enhanced Observations of Future Eruptions
To understand the processes that form oceanic crust as well as the role of submarine volcanoes in exchanging heat and chemicals with the ocean and in supporting chemosynthetic biological communities, it is essential to study underwater eruptions. The world’s most advanced underwater volcano observatory—the Ocean Observatories Initiative Cabled Array at Axial Seamount—builds upon ~30 years of sustained geophysical monitoring at this site with autonomous and remote systems. In April 2015, only months after the Cabled Array’s installation, it recorded an eruption at Axial Seamount, adding to the records of two prior eruptions in 1998 and 2011. Between eruptions, magma recharge is focused beneath the southeast part of the summit caldera, leading to steady inflation and increasing rates of seismicity. During each eruption, the volcano deflates over days to weeks, coincident with high levels of seismicity as a dike is emplaced along one of the volcano’s rifts and lava erupts on the seafloor. Cabled Array seismic data show that motions on an outward-dipping ring fault beneath the caldera accommodate the inflation and deflation. Eruptions appear to occur at a predictable level of inflation; hence, it should be possible to time deployments of additional cabled and autonomous instrumentation to further enhance observations of the next eruption
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