AIMC Topic: Image Processing, Computer-Assisted

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Assessment of deep learning-based PET attenuation correction frameworks in the sinogram domain.

Physics in medicine and biology
This study set out to investigate various deep learning frameworks for PET attenuation correction in the sinogram domain. Different models for both time-of-flight (TOF) and non-TOF PET emission data were implemented, including direct estimation of th...

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO challenge.

NeuroImage
Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the las...

FDRN: A fast deformable registration network for medical images.

Medical physics
PURPOSE: Deformable image registration is a fundamental task in medical imaging. Due to the large computational complexity of deformable registration of volumetric images, conventional iterative methods usually face the tradeoff between the registrat...

Automatic fetal biometry prediction using a novel deep convolutional network architecture.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Fetal biometric measurements face a number of challenges, including the presence of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid. This work proposes a convolutional neural network for automatic...

Classification of masked image data.

PloS one
Data classification is one of the most commonly used applications of machine learning. The are many developed algorithms that can work in various environments and for different data distributions that perform this task with excellence. Classification...

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

BJU international
OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant).

Toward autonomous robotic prostate biopsy: a pilot study.

International journal of computer assisted radiology and surgery
PURPOSE: We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and nee...

PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human motion prediction, which aims to predict future human poses given past poses, has recently seen increased interest. Many recent approaches are based on Recurrent Neural Networks (RNN) which model human poses with exponential maps. These approac...

Asbestos Detection with Fluorescence Microscopy Images and Deep Learning.

Sensors (Basel, Switzerland)
Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously developed software was not accurate for samples with low fiber concentration. Machine learning-base...

Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging.

Sensors (Basel, Switzerland)
Ultrasound breast imaging is a promising alternative to conventional mammography because it does not expose women to harmful ionising radiation and it can successfully image dense breast tissue. However, conventional ultrasound imaging only provides ...