AIMC Topic: Image Processing, Computer-Assisted

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Classification of foodborne bacteria using hyperspectral microscope imaging technology coupled with convolutional neural networks.

Applied microbiology and biotechnology
Foodborne pathogens have become ongoing threats in the food industry, whereas their rapid detection and classification at an early stage are still challenging. To address early and rapid detection, hyperspectral microscope imaging (HMI) technology co...

Logarithmic Fuzzy Entropy Function for Similarity Measurement in Multimodal Medical Images Registration.

Computational and mathematical methods in medicine
Multimodal medical images are useful for observing tissue structure clearly in clinical practice. To integrate multimodal information, multimodal registration is significant. The entropy-based registration applies a structure descriptor set to replac...

Disease Classification in Eggplant Using Pre-trained VGG16 and MSVM.

Scientific reports
Currently, the application of deep learning in crop disease classification is one of the active areas of research for which an image dataset is required. Eggplant (Solanum melongena) is one of the important crops, but it is susceptible to serious dis...

Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation.

IEEE transactions on medical imaging
Unsupervised domain adaptation has increasingly gained interest in medical image computing, aiming to tackle the performance degradation of deep neural networks when being deployed to unseen data with heterogeneous characteristics. In this work, we p...

Weighted discriminative collaborative competitive representation for robust image classification.

Neural networks : the official journal of the International Neural Network Society
Collaborative representation-based classification (CRC) is a famous representation-based classification method in pattern recognition. Recently, many variants of CRC have been designed for many classification tasks with the good classification perfor...

Segmenting skin ulcers and measuring the wound area using deep convolutional networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Bedridden patients presenting chronic skin ulcers often need to be examined at home. Healthcare professionals follow the evolution of the patients' condition by regularly taking pictures of the wounds, as different aspects ...

Pyramid feature adaptation for semi-supervised cardiac bi-ventricle segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cardiac bi-ventricle segmentation (BVS) is an essential task for assessing cardiac indices, such as the ejection fraction and volume of the left ventricle (LV) and right ventricle (RV). However, BVS is extremely challenging due to the high variabilit...

K-Anonymity inspired adversarial attack and multiple one-class classification defense.

Neural networks : the official journal of the International Neural Network Society
A novel adversarial attack methodology for fooling deep neural network classifiers in image classification tasks is proposed, along with a novel defense mechanism to counter such attacks. Two concepts are introduced, namely the K-Anonymity-inspired A...

Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.

BJU international
OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intelligence (AI) and image processing in a semi-automated fashion for tumour-to-cortex peak early-phase enhancement ratio (PEER) in order to differentiate CD...

PET image super-resolution using generative adversarial networks.

Neural networks : the official journal of the International Neural Network Society
The intrinsically low spatial resolution of positron emission tomography (PET) leads to image quality degradation and inaccurate image-based quantitation. Recently developed supervised super-resolution (SR) approaches are of great relevance to PET bu...