19 documents found, page 1 of 2
Adaptive feature recombination and recalibration for semantic segmentation with...
Pereira, Sergio; Pinto, Adriano; Amorim, Joana; Ribeiro, Alexandrine; Alves, Victor; Silva, Carlos A.Fully convolutional networks have been achieving remarkable results in image semantic segmentation, while being efficient. Such efficiency results from the capability of segmenting several voxels in a single forward pass. So, there is a direct spatial correspondence between a unit in a feature map and the voxel in the same location. In a convolutional layer, the kernel spans over all channels and extracts infor...
Modulation of urban atmospheric electric field measurements with the wind direc...
Silva, Hugo; Matthews, James; Conceição, Ricardo; Wright, Matthew; Pereira, Sergio; Reis, António; Shallcross, DudleyAtmospheric electric field measurements (potential gradient, PG) were retrieved in the urban environment of the city of Lisbon (Portugal). The measurements were performed with a Benndorf electrograph at the Portela Meteorological station in the suburbs of the city (NE from the centre). The period of 1980 to 1990 is considered here. According to wind direction, different content and types of ions and aerosols ar...
Saharan dust electrification perceived by a triangle of atmospheric electricity...
Silva, Hugo; Lopes, Francisco; Pereira, Sergio; Nicoll, Kery; Barbosa, Susana; Conceição, Ricardo; Neves, Samuel; Harrison, GilesAtmospheric Electric Potential Gradient (PG) measurements were carried out in three sites forming a triangular array in Southern Portugal. The campaign was performed during the summer, characterized by Saharan dust outbreaks; 16the17th July 2014 dust event is considered. Short time-scale oscillations of the PG at two of the stations and a mid time-scale suppression of the PG in the three stations are found. Res...
Segmentation squeeze-and-excitation blocks in stroke lesion outcome prediction
Amorim, Joana; Pinto, Adriano; Pereira, Sergio; Silva, Carlos A.Multi-modal Magnetic Resonance Imaging sequences along with 4D Perfusion Weighted Imaging scans provide important information for stroke lesion outcome prediction. However, the proposed methodologies until now were not able to discriminate correctly the most informative features from the less useful ones. In this work, we propose an enhanced version of a data fusion method for stroke tissue outcome prediction b...
Adaptive feature recombination and recalibration for semantic segmentation: app...
Pereira, Sergio; Alves, Victor; Silva, Carlos A.Convolutional neural networks (CNNs) have been successfully used for brain tumor segmentation, specifically, fully convolutional networks (FCNs). FCNs can segment a set of voxels at once, having a direct spatial correspondence between units in feature maps (FMs) at a given location and the corresponding classified voxels. In convolutional layers, FMs are merged to create new FMs, so, channel combination is cruc...
Retinal vessel segmentation based on Fully Convolutional Neural Networks
Oliveira, Americo; Pereira, Sergio; Silva, Carlos A.The retinal vascular condition is a reliable biomarker of several ophthalmologic and cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and monitor them. In this paper, we propose a novel method that combines the multiscale analysis provided by the Stationary Wavelet Transform with a multiscale Fully Convolutional Neural Network to cope with the varying width and direction of t...
Enhancing clinical MRI perfusion maps with data-driven maps of complementary na...
Pinto, Adriano; Pereira, Sergio; Meier, Raphael; Alves, Victor; Wiest, Roland; Silva, Carlos A.Stroke is the second most common cause of death in developed countries, where rapid clinical intervention can have a major impact on a patient’s life. To perform the revascularization procedure, the decision making of physicians considers its risks and benefits based on multi-modal MRI and clinical experience. Therefore, automatic prediction of the ischemic stroke lesion outcome has the potential to assist the ...
On hierarchical brain tumor segmentation in MRI using fully convolutional neura...
Pereira, Sergio; Oliveira, Americo; Alves, Victor; Silva, Carlos A.Magnetic Resonance Imaging is the preferred imaging modality for assessing brain tumors, and segmentation is necessary for diagnosis and treatment planning. Thus, robust automatic segmentation methods are required. Machine learning proposals where the model is learned from data are quite successful. Hierarchical segmentation approaches firstly segment the whole tumor, followed by intra-tumor tissue identificati...
Automatic brain tissue segmentation in MR images using Random Forests and Condi...
Pereira, Sergio; Pinto, Adriano; Oliveira, Jorge; Mendrik, Adrienne M.; Correia, J. H.; Silva, Carlos A.Background: The segmentation of brain tissue into cerebrospinal fluid, gray matter, and white matter in magnetic resonance imaging scans is an important procedure to extract regions of interest for quantitative analysis and disease assessment. Manual segmentation requires skilled experts, being a laborious and time-consuming task; therefore, reliable and robust automatic segmentation methods are necessary.New m...
Evaluation of the Use of a Disc-Saw Machine in Winter Pruning 'Rocha' Pear Orch...
Dias, Antonio B.; Patrocinio, Sandra; Pereira, Sergio; Brites, Teresa; Pita, Valério; Mota Barroso, JoãoManual pruning with pneumatic shears is a current practice used by pear ‘Rocha’ farmers in Portugal. However, is labour-intensive and therefore expensive. Work started in 2008 to study a mechanised alternative based on a discs-saw pruning machine mounted on a front loader of an agricultural tractor. The following three treatments were compared: T1 - manual pruning performed annually using pneumatic shears. T2 -...