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Debora Gil, & Petia Radeva. (2004). Inhibition of False Landmarks. In J. V. et al (Ed.), Recent Advances in Artificial Intelligence Research and Development (pp. 233–244). Barcelona (Spain): IOS Press.
Abstract: We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.
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Fernando Vilariño, Debora Gil, & Petia Radeva. (2004). A Novel FLDA Formulation for Numerical Stability Analysis. In P. R. and I. A. J. Vitrià (Ed.), Recent Advances in Artificial Intelligence Research and Development (Vol. 113, pp. 77–84). IOS Press.
Abstract: Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
Keywords: Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
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Judit Martinez, Eva Costa, P. Herreros, F. Javier Sanchez, & Ramon Baldrich. (2003). A Modular and Scalable Architecture for PC-Based Real-Time Vision Systems. Real–Time Imaging, (IF: 0.512), 9, 99–112.
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Eric Amiel. (2005). Visualisation de vaisseaux sanguins (Enric Marti, Ed.). Bachelor's thesis, Université Paul Sabatier Toulouse III, Toulouse.
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Marta Ligero, Alonso Garcia Ruiz, Cristina Viaplana, Guillermo Villacampa, Maria V Raciti, Jaid Landa, et al. (2021). A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors. Radiology, 299(1), 109–119.
Abstract: Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.
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G. Gasbarri, Matias Bilkis, E. Roda Salichs, & J. Calsamiglia. (2024). Sequential hypothesis testing for continuously-monitored quantum systems. Quantum, 8(1289).
Abstract: We consider a quantum system that is being continuously monitored, giving rise to a measurement signal. From such a stream of data, information needs to be inferred about the underlying system's dynamics. Here we focus on hypothesis testing problems and put forward the usage of sequential strategies where the signal is analyzed in real time, allowing the experiment to be concluded as soon as the underlying hypothesis can be identified with a certified prescribed success probability. We analyze the performance of sequential tests by studying the stopping-time behavior, showing a considerable advantage over currently-used strategies based on a fixed predetermined measurement time.
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Felipe Lumbreras, Joan Serrat, Ramon Baldrich, Maria Vanrell, & Juan J. Villanueva. (2001). Color Texture Recognition Through Multiresolution Features.
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Domicele Jonauskaite, Nele Dael, C. Alejandro Parraga, Laetitia Chevre, Alejandro Garcia Sanchez, & Christine Mohr. (2018). Stripping #The Dress: The importance of contextual information on inter-individual differences in colour perception. PSYCHO R - Psychological Research, , 1–15.
Abstract: In 2015, a picture of a Dress (henceforth the Dress) triggered popular and scientific interest; some reported seeing the Dress in white and gold (W&G) and others in blue and black (B&B). We aimed to describe the phenomenon and investigate the role of contextualization. Few days after the Dress had appeared on the Internet, we projected it to 240 students on two large screens in the classroom. Participants reported seeing the Dress in B&B (48%), W&G (38%), or blue and brown (B&Br; 7%). Amongst numerous socio-demographic variables, we only observed that W&G viewers were most likely to have always seen the Dress as W&G. In the laboratory, we tested how much contextual information is necessary for the phenomenon to occur. Fifty-seven participants selected colours most precisely matching predominant colours of parts or the full Dress. We presented, in this order, small squares (a), vertical strips (b), and the full Dress (c). We found that (1) B&B, B&Br, and W&G viewers had selected colours differing in lightness and chroma levels for contextualized images only (b, c conditions) and hue for fully contextualized condition only (c) and (2) B&B viewers selected colours most closely matching displayed colours of the Dress. Thus, the Dress phenomenon emerges due to inter-individual differences in subjectively perceived lightness, chroma, and hue, at least when all aspects of the picture need to be integrated. Our results support the previous conclusions that contextual information is key to colour perception; it should be important to understand how this actually happens.
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Mireia Forns-Nadal, Federico Sem, Anna Mane, Laura Igual, Dani Guinart, & Oscar Vilarroya. (2017). Increased Nucleus Accumbens Volume in First-Episode Psychosis. PRN - Psychiatry Research-Neuroimaging, 263, 57–60.
Abstract: Nucleus accumbens has been reported as a key structure in the neurobiology of schizophrenia. Studies analyzing structural abnormalities have shown conflicting results, possibly related to confounding factors. We investigated the nucleus accumbens volume using manual delimitation in first-episode psychosis (FEP) controlling for age, cannabis use and medication. Thirty-one FEP subjects who were naive or minimally exposed to antipsychotics and a control group were MRI scanned and clinically assessed from baseline to 6 months of follow-up. FEP showed increased relative and total accumbens volumes. Clinical correlations with negative symptoms, duration of untreated psychosis and cannabis use were not significant.
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Mohamed Ramzy Ibrahim, Robert Benavente, Daniel Ponsa, & Felipe Lumbreras. (2023). Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (Vol. 14469, 214–228). LNCS.
Abstract: Deep learning has made significant advances in recent years, and as a result, it is now in a stage where it can achieve outstanding results in tasks requiring visual understanding of scenes. However, its performance tends to decline when dealing with low-quality images. The advent of super-resolution (SR) techniques has started to have an impact on the field of remote sensing by enabling the restoration of fine details and enhancing image quality, which could help to increase performance in other vision tasks. However, in previous works, contradictory results for scene visual understanding were achieved when SR techniques were applied. In this paper, we present an experimental study on the impact of SR on enhancing aerial scene classification. Through the analysis of different state-of-the-art SR algorithms, including traditional methods and deep learning-based approaches, we unveil the transformative potential of SR in overcoming the limitations of low-resolution (LR) aerial imagery. By enhancing spatial resolution, more fine details are captured, opening the door for an improvement in scene understanding. We also discuss the effect of different image scales on the quality of SR and its effect on aerial scene classification. Our experimental work demonstrates the significant impact of SR on enhancing aerial scene classification compared to LR images, opening new avenues for improved remote sensing applications.
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Oriol Pujol, Petia Radeva, Jordi Vitria, & J. Mauri. (2004). Adaboost to Classify Plaque Appearance in IVUS Images.
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Santiago Segui, Laura Igual, Petia Radeva, Carolina Malagelada, Fernando Azpiroz, & Jordi Vitria. (2007). A Semi-Supervised Learning Method for Motility Disease Diagnostic. In Progress in Pattern Recognition, Image Analysis and Applications, 12th Iberoamerican Congress on Pattern (CIARP 2007), LCNS 4756:773–782, ISBN 978–3–540–76724–4.
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Sergio Escalera, Alicia Fornes, Oriol Pujol, Josep Llados, & Petia Radeva. (2007). Multi-class Binary Object Categorization using Blurred Shape Models. In Progress in Pattern Recognition, Image Analysis and Applications, 12th Iberoamerican Congress on Pattern (Vol. 4756, 773–782). LCNS.
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F. Javier Sanchez, & Jordi Vitria. (1994). ViLi + : Extended Lisp for image Processing and Computer Vision. In S.Impedovo (Ed.), Progress in Image Analysis and Processing III. World Scientific.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & Michael G. Strintzis. (2009). Prior Knowledge Based Motion Model Representation. In Horst Bunke, JuanJose Villanueva, & Gemma Sanchez (Eds.), Progress in Computer Vision and Image Analysis (Vol. 16).
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