AIMC Topic: Algorithms

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Deep learning based unpaired image-to-image translation applications for medical physics: a systematic review.

Physics in medicine and biology
. There is a growing number of publications on the application of unpaired image-to-image (I2I) translation in medical imaging. However, a systematic review covering the current state of this topic for medical physicists is lacking. The aim of this a...

Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations.

PloS one
Machine learning methods are widely used within the medical field. However, the reliability and efficacy of these models is difficult to assess, making it difficult for researchers to identify which machine-learning model to apply to their dataset. W...

Pill Box Text Identification Using DBNet-CRNN.

International journal of environmental research and public health
The recognition process of natural scenes is complicated at present, and images themselves may be complex owing to the special features of natural scenes. In this study, we use the detection and recognition of pill box text as an application scenario...

Computational Thinking Training and Deep Learning Evaluation Model Construction Based on Scratch Modular Programming Course.

Computational intelligence and neuroscience
To improve the algorithmic dimension, critical thinking, and problem-solving ability of computational thinking (CT) in students' programming courses, first, a programming teaching model is constructed based on the scratch modular programming course. ...

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark.

Medical image analysis
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robot...

Evaluation of real-time tumor contour prediction using LSTM networks for MR-guided radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Magnetic resonance imaging guided radiotherapy (MRgRT) with deformable multileaf collimator (MLC) tracking would allow to tackle both rigid displacement and tumor deformation without prolonging treatment. However, the system l...

Spatial resolution, noise properties, and detectability index of a deep learning reconstruction algorithm for dual-energy CT of the abdomen.

Medical physics
BACKGROUND: Iterative reconstruction (IR) has increasingly replaced traditional reconstruction methods in computed tomography (CT). The next paradigm shift in image reconstruction is likely to come from artificial intelligence, with deep learning rec...

Artificial intelligence based personalized predictive survival among colorectal cancer patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer is a major health concern. It is now the third most common cancer and the fourth leading cause of cancer mortality worldwide. The aim of this study was to evaluate the performance of machine learning algori...

Evaluation of thin-slice abdominal DECT using deep-learning image reconstruction in 74 keV virtual monoenergetic images: an image quality comparison.

Abdominal radiology (New York)
PURPOSE: To compare noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image quality using deep-learning image reconstruction (DLIR) vs. adaptive statistical iterative reconstruction (ASIR-V) in 0.625 and 2.5 mm slice thickness gra...

Morphology and mechanical performance of dental crown designed by 3D-DCGAN.

Dental materials : official publication of the Academy of Dental Materials
OBJECTIVES: This study utilised an Artificial Intelligence (AI) method, namely 3D-Deep Convolutional Generative Adversarial Network (3D-DCGAN), which is one of the true 3D machine learning methods, as an automatic algorithm to design a dental crown.