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Joint enhancement of automatic chest x-ray diagnosis and radiological gaze prediction with multistage cooperative learning

Author(s): Qiu Z; Rivaz H; Xiao Y;

Background: As visual inspection is an inherent process during radiological screening, the associated eye gaze data can provide valuable insights into relevant clinical decision processes and facilitate computer-assisted diagnosis. However, the relevant techniques are still under-explored. Purpose: With deep learning becoming the state-of-the-art for com ...

Article GUID: 40665596


Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations

Author(s): Gharamaleki SK; Helfield B; Rivaz H;

Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wavelength precision in microvasculature imaging by tracking gas microbubbles (MBs) flowing through blood vessels. However, MB localization faces challenges due to dynamic point spread functions (PSFs) caused by ...

Article GUID: 40640235


Ultrasound and MRI-based evaluation of relationships between morphological and mechanical properties of the lower lumbar multifidus muscle in chronic low back pain

Author(s): Naghdi N; Masi S; Bertrand C; Rosenstein B; Cohen-Adad J; Rivaz H; Roy M; Fortin M;

Purposes: While lumbar multifidus (MF) muscle alterations are linked to low back pain (LBP), the structure-function relationship is not fully understood. This study aims to evaluate the relationship between fatty degeneration of the lumbar MF muscle and its function in individuals with and without LBP. Methods: The study included 25 participants with chr ...

Article GUID: 40488869


CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke

Author(s): Aktar M; Tampieri D; Xiao Y; Rivaz H; Kersten-Oertel M;

Assessing collateral circulation is essential in determining the best treatment for ischemic stroke patients as good collaterals lead to different treatment options, i.e., thrombectomy, whereas poor collaterals can adversely affect the treatment by leading to excess bleeding and eventually death. To reduce inter- and intra-rater variability and save time ...

Article GUID: 40250214


Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models

Author(s): Gheflati B; Mirzaei M; Rottoo S; Rivaz H;

Purpose: Statistical shape models (SSMs) are widely used for morphological assessment of anatomical structures. However, a key limitation is the need for a clear relationship between the model's shape coefficients and clinically relevant anatomical parameters. To address this limitation, this paper proposes a novel deep learning-based anatomically par ...

Article GUID: 39953355


Open access segmentations of intraoperative brain tumor ultrasound images

Author(s): Behboodi B; Carton FX; Chabanas M; de Ribaupierre S; Solheim O; Munkvold BKR; Rivaz H; Xiao Y; Reinertsen I;

Purpose: Registration and segmentation of magnetic resonance (MR) and ultrasound (US) images could play an essential role in surgical planning and resectioning brain tumors. However, validating these techniques is challenging due to the scarcity of publicly accessible sources with high-quality gr ...

Article GUID: 39047165


Comparing a Portable Motion Analysis System against the Gold Standard for Potential Anterior Cruciate Ligament Injury Prevention and Screening

Author(s): Karatzas N; Abdelnour P; Corban JPAH; Zhao KY; Veilleux LN; Bergeron SG; Fevens T; Rivaz H; Babouras A; Martineau PA;

Knee kinematics during a drop vertical jump, measured by the Kinect V2 (Microsoft, Redmond, WA, USA), have been shown to be associated with an increased risk of non-contact anterior cruciate ligament injury. The accuracy and reliability of the Microsoft Kinect V2 has yet to be assessed specifical ...

Article GUID: 38544237


SCANED: Siamese collateral assessment network for evaluation of collaterals from ischemic damage

Author(s): Aktar M; Xiao Y; Tehrani AKZ; Tampieri D; Rivaz H; Kersten-Oertel M;

This study conducts collateral evaluation from ischemic damage using a deep learning-based Siamese network, addressing the challenges associated with a small and imbalanced dataset. The collateral network provides an alternative oxygen and nutrient supply pathway in ischemic stroke cases, influencing treatment decisions. Research in this area focuses on a ...

Article GUID: 38364600


On the soft tissue ultrasound elastography using FEM based inversion approach

Author(s): Eshaghinia SS; Taghvaeipour A; Aghdam MM; Rivaz H;

Elastography is a medical imaging modality that enables visualization of tissue stiffness. It involves quasi-static or harmonic mechanical stimulation of the tissue to generate a displacement field which is used as input in an inversion algorithm to reconstruct tissue elastic modulus. This paper considers quasi-static stimulation and presents a novel inve ...

Article GUID: 38240143


Bayesian workflow for the investigation of hierarchical classification models from tau-PET and structural MRI data across the Alzheimer's disease spectrum

Author(s): Belasso CJ; Cai Z; Bezgin G; Pascoal T; Stevenson J; Rahmouni N; Tissot C; Lussier F; Rosa-Neto P; Soucy JP; Rivaz H; Benali H;

Background: Alzheimer's disease (AD) diagnosis in its early stages remains difficult with current diagnostic approaches. Though tau neurofibrillary tangles (NFTs) generally follow the stereotypical pattern described by the Braak staging scheme, the network degeneration hypothesis (NDH) has su ...

Article GUID: 37920382


Deep learning for collateral evaluation in ischemic stroke with imbalanced data

Author(s): Aktar M; Reyes J; Tampieri D; Rivaz H; Xiao Y; Kersten-Oertel M;

Purpose: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods in treatment decision-making.
Methods: We adapted a pre-trained Eff ...

Article GUID: 36635594


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