AIMC Topic: Image Processing, Computer-Assisted

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Unsupervised SoftOtsuNet Augmentation for Clinical Dermatology Image Classifiers.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Data Augmentation is a crucial tool in the Machine Learning (ML) toolbox because it can extract novel, useful training images from an existing dataset, thereby improving accuracy and reducing overfitting in a Deep Neural Network (DNNs). However, clin...

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

Physical and engineering sciences in medicine
MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from on...

End-to-end volumetric segmentation of white matter hyperintensities using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Reliable detection of white matter hyperintensities (WMH) is crucial for studying the impact of diffuse white-matter pathology on brain health and monitoring changes in WMH load over time. However, manual annotation of 3D h...

Strategies for deep learning-based attenuation and scatter correction of brain F-FDG PET images in the image domain.

Medical physics
BACKGROUND: Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/M...

Deep learning-based association analysis of root image data and cucumber yield.

The Plant journal : for cell and molecular biology
The root system is important for the absorption of water and nutrients by plants. Cultivating and selecting a root system architecture (RSA) with good adaptability and ultrahigh productivity have become the primary goals of agricultural improvement. ...

Deep learning-accelerated image reconstruction in MRI of the orbit to shorten acquisition time and enhance image quality.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: This study explores the use of deep learning (DL) techniques in MRI of the orbit to enhance imaging. Standard protocols, although detailed, have lengthy acquisition times. We investigate DL-based methods for T2-weighted and T1...

DeepPyramid+: medical image segmentation using Pyramid View Fusion and Deformable Pyramid Reception.

International journal of computer assisted radiology and surgery
PURPOSE: Semantic segmentation plays a pivotal role in many applications related to medical image and video analysis. However, designing a neural network architecture for medical image and surgical video segmentation is challenging due to the diverse...

Automated Measurement of Ovary Development in Atlantic Salmon Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: Salmon breeding companies control the egg stripping period through environmental change, which triggers the need to identify the state of maturation. Ultrasound imaging of the salmon ovary is a proven non-invasive tool for this purpose; ho...

A convolutional neural network-based method for the generation of super-resolution 3D models from clinical CT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The accurate evaluation of bone mechanical properties is essential for predicting fracture risk based on clinical computed tomography (CT) images. However, blurring and noise in clinical CT images can compromise the accuracy...

MicroSegNet: A deep learning approach for prostate segmentation on micro-ultrasound images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides 3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost, accurate diagnosis of prostate cancer. Accurate prostate segmentation is crucial ...