15 documents found, page 1 of 2
Detection of bladder cancer with feature fusion, transfer learning and CapsNets
Freitas, Nuno Renato Azevedo; Vieira, Pedro Miguel; Cordeiro, Agostinho; Tinoco, Catarina; Morais, Nuno; Torres, João Nuno Braga PimentelThis paper confronts two approaches to classify bladder lesions shown in white light cystoscopy images when using small datasets: the classical one, where handcrafted-based features feed pattern recognition systems and the modern deep learning-based (DL) approach. In between, there are alternative DL models that had not received wide attention from the scientific community, even though they can be more appropri...
Clinical performance of new software to automatically detect angioectasias in s...
Costa, Dalila Amélia Amorim; Vieira, Pedro Miguel; Pinto, Catarina; Arroja, Bruno; Leal, Tiago; Mendes, Sofia Silva; Gonçalves, Raquel; Lima, C. S.Background: Video capsule endoscopy (VCE) revolutionized the diagnosis and management of obscure gastrointestinal bleeding, though the rate of detection of small bowel lesions by the physician is still disappointing. Our group developed a novel algorithm (CMEMS-Uminho) to automatically detect angioectasias which display greater accuracy in VCE static frames than other methods previously published. We aimed to e...
Multi-pathology detection and lesion localization in WCE videos by using the in...
Vieira, Pedro Miguel; Freitas, Nuno Renato Azevedo; Lima, Veríssimo B.; Costa, Dalila Amélia Amorim; Rolanda, Carla; Lima, C. S.The majority of current systems for automatic diagnosis considers the detection of a unique and previously known pathology. Considering specifically the diagnosis of lesions in the small bowel using endoscopic capsule images, very few consider the possible existence of more than one pathology and when they do, they are mainly detection based systems therefore unable to localize the suspected lesions. Such syste...
Hierarchical classification of lesions in wireless capsule endoscopy exams
Vieira, Pedro MiguelA cápsula endoscópica é um dispositivo médico que tem como como principal vantagem a possibilidade de visualizar todo o trato gastrointestinal. Este exame não invasivo é especialmente usado e vantajoso para o diagnóstico de patologias do intestino delgado, já que a endoscopia convencional é um exame invasivo que não possibilita a visualização deste órgão. Para analisar os exames de cápsula endoscópica o pessoal...
Combination of color-based segmentation, Markov random fields and multilayer pe...
Vieira, Pedro Miguel; Freitas, Nuno Renato; Rolanda, Carla; Lima, C. S.Angioectasias are lesions characterized by specific features, related to their color and shape. Since the high prevalence of angioectasias in the small bowel, it is of great importance the development of a method to correctly localize these lesions within the intestinal tissue. Since the differences found in the color of the lesions, when compared with other lesions and the normal tissue, it was developed a met...
Automatic detection of small bowel tumors in wireless capsule endoscopy images ...
Vieira, Pedro Miguel; Freitas, Nuno Renato Azevedo; Valente, João; Vaz, A. Ismael F.; Rolanda, Carla; Lima, C. S.Purpose Wireless Capsule Endoscopy (WCE) is a minimally invasive diagnosis tool for lesion detection in the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the significant amount of acquired data leads to difficulties in the diagnosis by the physicians; which can be eased with computer assistance. This paper addresses a method for the automatic detection of tumors in ...
Brain extraction in partial volumes T2*@7T by using a quasi-anatomic segmentati...
Valente, João; Vieira, Pedro Miguel; Couto, Carlos; Lima, C. S.Background Poor brain extraction in Magnetic Resonance Imaging (MRI) has negative consequences in several types of brain post-extraction such as tissue segmentation and related statistical measures or pattern recognition algorithms. Current state of the art algorithms for brain extraction work on weighted T1 and T2, being not adequate for non-whole brain images such as the case of T2*FLASH@7T partial volumes. N...
Automatic T1 bladder tumor detection by using wavelet analysis in cystoscopy im...
Freitas, Nuno R.; Vieira, Pedro Miguel; Lima, Estêvão Augusto Rodrigues de; Lima, C. S.Correct classification of cystoscopy images depends on the interpreter's experience. Bladder cancer is a common lesion that can only be confirmed by biopsying the tissue, therefore, the automatic identification of tumors plays a significant role in early stage diagnosis and its accuracy. To our best knowledge, the use of white light cystoscopy images for bladder tumor diagnosis has not been reported so far. In ...
Using cystoscopy to segment bladder tumors with a multivariate approach in diff...
Freitas, Nuno R.; Vieira, Pedro Miguel; Lima, Estêvão Augusto Rodrigues de; Lima, C. S.Nowadays the diagnosis of bladder lesions relies upon cystoscopy examination and depends on the interpreter's experience. State of the art of bladder tumor identification are based on 3D reconstruction, using CT images (Virtual Cystoscopy) or images where the structures are exalted with the use of pigmentation, but none uses white light cystoscopy images. An initial attempt to automatically identify tumoral tis...
Ensemble learning based classification for BCI applications
Silva, Vitor F.; Barbosa, Roberto M.; Vieira, Pedro Miguel; Lima, C. S.This paper reports the use of combinations of multiple learning models, a type of structure called ensemble system in the classification of movement imagination, an interesting topic in the Brain Computer Interface (BCI) field. The considered models are the well-known Multilayer Perceptron (MLP), perhaps the most often used Neural Network (NN) based models. The proposed method has been applied on the Graze data...