AIMC Topic: Image Processing, Computer-Assisted

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Medical image segmentation network based on multi-scale frequency domain filter.

Neural networks : the official journal of the International Neural Network Society
With the development of deep learning, medical image segmentation in computer-aided diagnosis has become a research hotspot. Recently, UNet and its variants have become the most powerful medical image segmentation methods. However, these methods suff...

Frequency compensated diffusion model for real-scene dehazing.

Neural networks : the official journal of the International Neural Network Society
Due to distribution shift, deep learning based methods for image dehazing suffer from performance degradation when applied to real-world hazy images. In this paper, this study considers a dehazing framework based on conditional diffusion models for i...

HGCMorph: joint discontinuity-preserving and pose-learning via GNN and capsule networks for deformable medical images registration.

Physics in medicine and biology
This study aims to enhance medical image registration by addressing the limitations of existing approaches that rely on spatial transformations through U-Net, ConvNets, or Transformers. The objective is to develop a novel architecture that combines C...

Face anti-spoofing with cross-stage relation enhancement and spoof material perception.

Neural networks : the official journal of the International Neural Network Society
Face Anti-Spoofing (FAS) seeks to protect face recognition systems from spoofing attacks, which is applied extensively in scenarios such as access control, electronic payment, and security surveillance systems. Face anti-spoofing requires the integra...

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization.

BMC bioinformatics
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an intera...

Deep local-to-global feature learning for medical image super-resolution.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical images play a vital role in medical analysis by providing crucial information about patients' pathological conditions. However, the quality of these images can be compromised by many factors, such as limited resolution of the instruments, art...

The multimodality cell segmentation challenge: toward universal solutions.

Nature methods
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different exp...

A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Automatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning based network to detect HCC from ...

Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.

Journal of imaging informatics in medicine
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...

DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus.

Journal of imaging informatics in medicine
Depth of focus (DOF) is defined as the axial range in which the specimen stage moves without losing focus while the imaging apparatus remains stable. It may not be possible to capture an image that includes the entire specimen in focus due to the nar...