AIMC Topic: Retrospective Studies

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MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

Physics in medicine and biology
Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy and reliability of target delineation due to its superior soft tissue contrast over CT. The MRI-onl...

Automated identification of malignancy in whole-slide pathological images: identification of eyelid malignant melanoma in gigapixel pathological slides using deep learning.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop a deep learning system (DLS) that can automatically detect malignant melanoma (MM) in the eyelid from histopathological sections with colossal information density.

Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diffusion-weighted imaging (DWI) in MRI plays an increasingly important role in diagnostic applications and developing imaging biomarkers. Automated whole-breast segmentation is an important yet challenging step for quantitative breast im...

Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration.

Journal of the American College of Surgeons
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and earlier models include data not available at the time of scheduling. Our objective was to develop stat...

Image-Guided Robotic Radiosurgery for Treatment of Recurrent Grade II and III Meningiomas. A Single-Center Study.

World neurosurgery
OBJECTIVE: Stereotactic radiosurgery (SRS) has been increasingly applied for malignant meningiomas as an alternative to conventionally fractioned radiation therapy. We performed a retrospective analysis of an institutional patient cohort with maligna...

Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT).

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre-trained deep learning model to interpret routine projection kilovoltage (kV) X-ray images in image-guided radiation therapy (IGRT).

Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definition guidelines use anatomic MRI (magnetic resonance imaging) scans, taking into account contrast enhancement and the rather unspecific hyperintensity o...

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

The British journal of radiology
OBJECTIVE: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT as metastatic and completely responded in pa...

Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

World neurosurgery
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.

A robust machine learning enabled decomposition of shear ground reaction forces during the double contact phase of walking.

Gait & posture
BACKGROUND: Dynamic analyses of walking rely on the 3D ground reaction forces (GRF) under each foot, while only the resultant force of both limbs may be recorded on a single-belt instrumented treadmill or when both feet touch the same force platform.