Gemma Piella

Bio: Gemma Piella is an academic researcher from Pompeu Fabra University. The author has contributed to research in topics: Computer science & Lifting scheme. The author has an hindex of 25, co-authored 143 publications receiving 4411 citations. Previous affiliations of Gemma Piella include Autonomous University of Barcelona & Polytechnic University of Catalonia.

Quasi-Conformal Technique for Integrating and Validating Myocardial Tissue Characterization in MRI with Ex-Vivo Human Histological Data

Abstract: Ventricular tachycardia caused by a circuit of re-entry is one of the most critical arrhythmias. It is usually related with heterogeneous scar regions where slow velocity of conduction tissue is mixed with non-conductive tissue, creating pathways (CC) responsible for the tachycardia. Pre-operative DE-MRI can provide information on myocardial tissue viability and then improve therapy planning. However, the current DE-MRI resolution is not sufficient for identifying small CCs and therefore they have to be identified during the intervention, which requires considerable operator experience. In this work, we studied the relationship of histological data (with 10 \(\mu \)m resolution), with in-vivo DE-MRI pixel intensities (PI) of one human heart. Integrating multi-modal data provided by different nature (in- vs. ex-vivo; 3D volume vs. 2D slices) is not straightforward and requires a robust integration pipeline. The main purpose of this work, is to develop a new technique for integrating histological information into the corresponding DE-MRI one. The proposed quasi-conformal mapping technique (QCM) integration were compared with state-of-the-art registration techniques (affine and non-rigid) on a benchmark of 418 synthetically generated datasets showing a more robust results. We used the QCM to quantitatively compare DE-MRI PI with the percentage of fibrosis extracted from histology. We show a positive correlation between the DE-MRI PI and the percentage of fibrosis extracted from histology (r = 0.97; p 60\(\%\) of the maximum intensity value).

Localizing Cardiac Dyssynchrony in M-mode Echocardiography with Attention Maps

Abstract: Cardiac Resynchronization Therapy (CRT) is a treatment aimed at restoring the electrical synchronization in patients with heart failure and intraventricular conduction delay. However, over 30% of patients do not respond to CRT. Septal Flash (SF), an abnormality characterized by a rapid inward-outward abnormal motion at early systole, has been linked to an improved response to CRT in patients with Left Bundle Branch Block (LBBB). In clinical practice, the detection of SF is usually performed manually through echocardiographic acquisitions, which is subjective and dependent on the operator’s experience. To address this issue, a deep classification model for automatic SF detection from 2D anatomical M-mode images has been proposed. Additionally, this work focuses on SF localization from gradient-based attention maps, which provide a visual explanation of the output prediction of the model. Two models based on convolutional neural networks (CNNs) were trained with original and cropped M-modes from 143 patients, and achieved an accuracy of 0.83 and 1.0 respectively, on 29 testing patients. The attention map visualization showed that in SF cases, the models effectively identified the discriminant regions, while in non-SF cases, the maps appeared more dispersed. Further research is necessary to quantitatively evaluate the attention map results.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures

Abstract: In this article, we have reviewed the reasons why we (collectively) want to love or leave the venerable (but perhaps hoary) MSE. We have also reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems. The message we are trying to send here is not that one should abandon use of the MSE nor to blindly switch to any other particular signal fidelity measure. Rather, we hope to make the point that there are powerful, easy-to-use, and easy-to-understand alternatives that might be deployed depending on the application environment and needs. While we expect (and indeed, hope) that the MSE will continue to be widely used as a signal fidelity measure, it is our greater desire to see more advanced signal fidelity measures being used, especially in applications where perceptual criteria might be relevant. Ideally, the performance of a new signal processing algorithm might be compared to other algorithms using several fidelity criteria. Lastly, we hope that we have given further motivation to the community to consider recent advanced signal fidelity measures as design criteria for optimizing signal processing algorithms and systems. It is in this direction that we believe that the greatest benefit eventually lies.

Data fusion

Abstract: The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation.This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

Image Fusion With Guided Filtering

Abstract: A fast and effective image fusion method is proposed for creating a highly informative fused image through merging multiple images. The proposed method is based on a two-scale decomposition of an image into a base layer containing large scale variations in intensity, and a detail layer capturing small scale details. A novel guided filtering-based weighted average technique is proposed to make full use of spatial consistency for fusion of the base and detail layers. Experimental results demonstrate that the proposed method can obtain state-of-the-art performance for fusion of multispectral, multifocus, multimodal, and multiexposure images.