AIMC Topic: Deep Learning

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[Multimodal imaging and evaluation in the age of artificial intelligence].

Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft
Multimodal imaging is able to image the retina in unprecedented detail, and the joint analysis (integration) of these data not only enables the securing of diagnoses, but also a more precise definition; however, humans encounter temporal and cognitiv...

Model-to-Data Approach for Deep Learning in Optical Coherence Tomography Intraretinal Fluid Segmentation.

JAMA ophthalmology
IMPORTANCE: Amid an explosion of interest in deep learning in medicine, including within ophthalmology, concerns regarding data privacy, security, and sharing are of increasing importance. A model-to-data approach, in which the model itself is transf...

Binary Classification of Alzheimer's Disease Using sMRI Imaging Modality and Deep Learning.

Journal of digital imaging
Alzheimer's disease (AD) is an irreversible devastative neurodegenerative disorder associated with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for the development of possible future treatment option(s). St...

Deep Learning Pre-training Strategy for Mammogram Image Classification: an Evaluation Study.

Journal of digital imaging
In this work, we assess how pre-training strategy affects deep learning performance for the task of distinguishing false-recall from malignancy and normal (benign) findings in digital mammography images. A cohort of 1303 breast cancer screening patie...

Advanced Deep Learning Techniques Applied to Automated Femoral Neck Fracture Detection and Classification.

Journal of digital imaging
To use deep learning with advanced data augmentation to accurately diagnose and classify femoral neck fractures. A retrospective study of patients with femoral neck fractures was performed. One thousand sixty-three AP hip radiographs were obtained fr...

Deep Learning for Virtual Histological Staining of Bright-Field Microscopic Images of Unlabeled Carotid Artery Tissue.

Molecular imaging and biology
PURPOSE: Histological analysis of artery tissue samples is a widely used method for diagnosis and quantification of cardiovascular diseases. However, the variable and labor-intensive tissue staining procedures hinder efficient and informative histolo...

Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.