AIMC Topic: Feasibility Studies
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Hardware-Independent Deep Signal Processing: A Feasibility Study in Echocardiography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Deep learning (DL) models have emerged as alternative methods to conventional ultrasound (US) signal processing, offering the potential to mimic signal processing chains, reduce inference time, and enable the portability of processing chains across h...
Feasibility study of machine learning to explore relationships between antimicrobial resistance and microbial community structure in global wastewater treatment plant sludges.
Bioresource technology
Nov 26, 2024
Wastewater sludges (WSs) are major reservoirs and emission sources of antibiotic resistance genes (ARGs) in cities. Identifying antimicrobial resistance (AMR) host bacteria in WSs is crucial for understanding AMR formation and mitigating biological a...
Detecting Collagen by Machine Learning Improved Photoacoustic Spectral Analysis for Breast Cancer Diagnostics: Feasibility Studies With Murine Models.
Journal of biophotonics
Nov 26, 2024
Collagen, a key structural component of the extracellular matrix, undergoes significant remodeling during carcinogenesis. However, the important role of collagen levels in breast cancer diagnostics still lacks effective in vivo detection techniques t...
Telerehabilitation using a 2-D planar arm rehabilitation robot for hemiparetic stroke: a feasibility study of clinic-to-home exergaming therapy.
Journal of neuroengineering and rehabilitation
Nov 26, 2024
BACKGROUND: We evaluated the feasibility, safety, and efficacy of a 2D-planar robot for minimally supervised home-based upper-limb therapy for post-stroke hemiparesis.
Reproducing the caress gesture with an anthropomorphic robot: a feasibility study.
Bioinspiration & biomimetics
Nov 22, 2024
Social robots have been widely used to deliver emotional, cognitive and social support to humans. The exchange of affective gestures, instead, has been explored to a lesser extent, despite phyisical interaction with social robots could provide the sa...
A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.
Acta radiologica (Stockholm, Sweden : 1987)
Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Deep learning-based automatic bleeding recognition during liver resection in laparoscopic hepatectomy.
Surgical endoscopy
Nov 18, 2024
BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for negative postoperative outcomes. Ensuring appropriate hemostasis enhances the safety of surgical procedures. An automatic bleeding recognition system base...
Technical feasibility of automated blur detection in digital mammography using convolutional neural network.
European radiology experimental
Nov 18, 2024
BACKGROUND: The presence of a blurred area, depending on its localization, in a mammogram can limit diagnostic accuracy. The goal of this study was to develop a model for automatic detection of blur in diagnostically relevant locations in digital mam...
Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.
Journal of applied clinical medical physics
Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Radiation Dosage
Signal-To-Noise Ratio
Pelvic Neoplasms
Radiotherapy Dosage
Radiographic Image Interpretation, Computer-Assisted
Feasibility Studies
Organs at Risk
Radiotherapy Planning, Computer-Assisted
Radiographic Image Enhancement
Radiotherapy, Intensity-Modulated
Phantoms, Imaging
Abdominal Neoplasms
Radiotherapy, Image-Guided
Humans
Algorithms
Prospective Studies
Tomography, X-Ray Computed
Female
Male
Deep Learning
Image Processing, Computer-Assisted
In vivo evaluation of complex polyps with endoscopic optical coherence tomography and deep learning during routine colonoscopy: a feasibility study.
Scientific reports
Nov 14, 2024
Standard-of-care (SoC) imaging for assessing colorectal polyps during colonoscopy, based on white-light colonoscopy (WLC) and narrow-band imaging (NBI), does not have sufficient accuracy to assess the invasion depth of complex polyps non-invasively d...
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