AIMC Topic: Image Processing, Computer-Assisted

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Machine learning-based cytokine microarray digital immunoassay analysis.

Biosensors & bioelectronics
Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short ...

Translating amyloid PET of different radiotracers by a deep generative model for interchangeability.

NeuroImage
It is challenging to compare amyloid PET images obtained with different radiotracers. Here, we introduce a new approach to improve the interchangeability of amyloid PET acquired with different radiotracers through image-level translation. Deep genera...

Training deep-learning segmentation models from severely limited data.

Medical physics
PURPOSE: To enable generation of high-quality deep learning segmentation models from severely limited contoured cases (e.g., ~10 cases).

A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution.

Sensors (Basel, Switzerland)
Colon carcinoma is one of the leading causes of cancer-related death in both men and women. Automatic colorectal polyp segmentation and detection in colonoscopy videos help endoscopists to identify colorectal disease more easily, making it a promisin...

Deep learning based automated diagnosis of bone metastases with SPECT thoracic bone images.

Scientific reports
SPECT nuclear medicine imaging is widely used for treating, diagnosing, evaluating and preventing various serious diseases. The automated classification of medical images is becoming increasingly important in developing computer-aided diagnosis syste...

An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning.

Nature communications
Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole-slide images (WSIs). Most studies have employed patch-based methods, which often require detailed annotation of image patches. This typically involves l...

AI-based mobile application to fight antibiotic resistance.

Nature communications
Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse. While disk diffusion antibiotic susceptibility testing (AST, also called antibiogram) is broadly used to test for antibiotic resistance in ...

Medical Image Classification Algorithm Based on Visual Attention Mechanism-MCNN.

Oxidative medicine and cellular longevity
Due to the complexity of medical images, traditional medical image classification methods have been unable to meet the actual application needs. In recent years, the rapid development of deep learning theory has provided a technical approach for solv...

Improving blood cells classification in peripheral blood smears using enhanced incremental training.

Computers in biology and medicine
Peripheral Blood Smear (PBS) analysis is a vital routine test carried out by medical specialists to assess some health aspects of individuals. The automation of blood analysis has attracted the attention of researchers in recent years, as it will not...

Image synthesis of monoenergetic CT image in dual-energy CT using kilovoltage CT with deep convolutional generative adversarial networks.

Journal of applied clinical medical physics
PURPOSE: To synthesize a dual-energy computed tomography (DECT) image from an equivalent kilovoltage computed tomography (kV-CT) image using a deep convolutional adversarial network.