Concept

Computer-aided diagnosis

Related publications (190)

Trustworthy Face Recognition: Improving Generalization of Deep Face Presentation Attack Detection

The extremely high recognition accuracy achieved by modern, convolutional neural network (CNN) based face recognition (FR) systems has contributed significantly to the adoption of such systems in a variety of applications, from mundane activities like unlo ...

EPFL2020

RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis

Meritxell Bach Cuadra, Tobias Kober, Cristina Granziera, Francesco La Rosa, Hamza Kebiri, Po-Jui Lu

Objectives In multiple sclerosis (MS), the presence of a paramagnetic rim at the edge of non-gadolinium-enhancing lesions indicates perilesional chronic inflammation. Patients featuring a higher paramagnetic rim lesion burden tend to have more aggressive d ...

2020

Automatic 12-lead ECG Classification Using a Convolutional Network Ensemble

Manoel Horta Ribeiro

The 12-lead electrocardiogram (ECG) is a major diagnostic test for cardiovascular diseases and enhanced automated analysis tools might lead to more reliable diagnosis and improved clinical practice. Deep neural networks are models composed of stacked trans ...

IEEE2020

Multi-Channel Front-End for Electrochemical Sensing of Metabolites, Drugs, and Electrolytes

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Francesca Criscuolo, Nadezda Pankratova

A multi-channel front-end for electrochemical sensing is presented. It consists of a multiplexed four-channel readout interface supporting amperometric, voltammetric, and potentiometric measurements. The electronic interface is co-designed according to the ...

2020

Spiking Neural Networks Trained With Backpropagation For Low Power Neuromorphic Implementation Of Voice Activity Detection

Milos Cernak, Giorgia Dellaferrera

Recent advances in Voice Activity Detection (VAD) are driven by artificial and Recurrent Neural Networks (RNNs), however, using a VAD system in battery-operated devices requires further power efficiency. This can be achieved by neuromorphic hardware, which ...

IEEE2020

Resting-state EEG topographies: Reliable and sensitive signatures of unilateral spatial neglect

Dimitri Nestor Alice Van De Ville, Elvira Pirondini

Theoretical advances in the neurosciences are leading to the development of an increasing number of proposed interventions for the enhancement of functional recovery after brain damage. Integration of these novel approaches in clinical practice depends on ...

2020

On the Evaluation and Real-World Usage Scenarios of Deep Vessel Segmentation for Funduscopy

André Anjos

We identify and address three research gaps in the field of vessel segmentation for funduscopy. The first focuses on the task of inference on high-resolution fundus images for which only a limited set of ground-truth data is publicly available. Notably, we ...

Idiap2019

Automatic Diagnosis of Alzheimer's Disease Using Neural Network Language Models

Julian David Fritsch

In today’s aging society, the number of neurodegenerative dis-eases such as Alzheimer’s disease (AD) increases. Reliable tools forautomatic early screening as well as monitoring of AD patients arenecessary. For that, semantic deficits have been shown to be ...

IEEE2019

Recurrent U-Net for Resource-Constrained Segmentation

Pascal Fua, Mathieu Salzmann, Joachim Ludovic Hugonot, Wei Wang, Kaicheng Yu

State-of-the-art segmentation methods rely on very deep networks that are not always easy to train without very large training datasets and tend to be relatively slow to run on standard GPUs. In this paper, we introduce a novel recurrent U-Net architecture ...

IEEE COMPUTER SOC2019

Detecting the Unexpected via Image Resynthesis

Pascal Fua, Mathieu Salzmann, Krzysztof Maciej Lis, Krishna Kanth Nakka

Classical semantic segmentation methods, including the recent deep learning ones, assume that all classes observed at test time have been seen during training. In this paper, we tackle the more realistic scenario where unexpected objects of unknown classes ...

IEEE2019

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