AIMC Topic: Image Processing, Computer-Assisted

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Graph Flow: Cross-Layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation.

IEEE transactions on medical imaging
With the development of deep convolutional neural networks, medical image segmentation has achieved a series of breakthroughs in recent years. However, high-performance convolutional neural networks always mean numerous parameters and high computatio...

Reproducibility of linear and angular cephalometric measurements obtained by an artificial-intelligence assisted software (WebCeph) in comparison with digital software (AutoCEPH) and manual tracing method.

Dental press journal of orthodontics
INTRODUCTION: It has been suggested that human errors during manual tracing of linear/angular cephalometric parameters can be eliminated by using computer-aided analysis. The landmarks, however, are located manually and the computer system completes ...

Report on the AAPM deep-learning spectral CT Grand Challenge.

Medical physics
BACKGROUND: This Special Report summarizes the 2022 AAPM Grand Challenge on Deep-Learning spectral Computed Tomography (DL-spectral CT) image reconstruction.

Aggregated micropatch-based deep learning neural network for ultrasonic diagnosis of cirrhosis.

Artificial intelligence in medicine
Despite the advancements in the diagnosis of early-stage cirrhosis, the accuracy in the diagnosis using ultrasound is still challenging owing to the presence of various image artifacts, which results in poor visual quality of the textural and lower-f...

BiTNet: Hybrid deep convolutional model for ultrasound image analysis of human biliary tract and its applications.

Artificial intelligence in medicine
Certain life-threatening abnormalities, such as cholangiocarcinoma, in the human biliary tract are curable if detected at an early stage, and ultrasonography has been proven to be an effective tool for identifying them. However, the diagnosis often r...

Transformer guided progressive fusion network for 3D pancreas and pancreatic mass segmentation.

Medical image analysis
Pancreatic masses are diverse in type, often making their clinical management challenging. This study aims to address the task of various types of pancreatic mass segmentation and detection while accurately segmenting the pancreas. Although convoluti...

Dental image enhancement network for early diagnosis of oral dental disease.

Scientific reports
Intelligent robotics and expert system applications in dentistry suffer from identification and detection problems due to the non-uniform brightness and low contrast in the captured images. Moreover, during the diagnostic process, exposure of sensiti...

Synthesis of large scale 3D microscopic images of 3D cell cultures for training and benchmarking.

PloS one
The analysis of 3D microscopic cell culture images plays a vital role in the development of new therapeutics. While 3D cell cultures offer a greater similarity to the human organism than adherent cell cultures, they introduce new challenges for autom...

Active mesh and neural network pipeline for cell aggregate segmentation.

Biophysical journal
Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline comb...

Application of image processing and transfer learning for the detection of rust disease.

Scientific reports
Plant diseases introduce significant yield and quality losses to the food production industry, worldwide. Early identification of an epidemic could lead to more effective management of the disease and potentially reduce yield loss and limit excessive...