AIMC Topic: Image Processing, Computer-Assisted

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Importance of dataset design in developing robust U-Net models for label-free cell morphology evaluation.

Journal of bioscience and bioengineering
Advances in regenerative medicine highlighted the need for label-free cell image analysis to replace conventional microscopic observation for non-invasive cell quality evaluation. Image-based evaluation provides an efficient, quantitative, and automa...

Self-supervision advances morphological profiling by unlocking powerful image representations.

Scientific reports
Cell Painting is an image-based assay that offers valuable insights into drug mechanisms of action and off-target effects. However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter...

Scaling Synthetic Brain Data Generation.

IEEE journal of biomedical and health informatics
The limited availability of diverse, high-quality datasets is a significant challenge in applying deep learning to neuroimaging research. Although synthetic data generation can potentially address this issue, on-the-fly generation is computationally ...

EDSRNet: An Enhanced Decoder Semantic Recovery Network for 2D Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In recent years, with the advancement of medical imaging technology, medical image segmentation has played a key role in assisting diagnosis and treatment planning. Current deep learning-based medical image segmentation methods mainly adopt encoder-d...

CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.

IEEE journal of biomedical and health informatics
In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of bone cancers due to its high sensitivity to malignant tumors. The diagnosis of bone cancer requires tumor analysis and localization, where accurate a...

Attention-Based Q-Space Deep Learning Generalized for Accelerated Diffusion Magnetic Resonance Imaging.

IEEE journal of biomedical and health informatics
Diffusion magnetic resonance imaging (dMRI) is a non-invasive method for capturing the microanatomical information of tissues by measuring the diffusion weighted signals along multiple directions, which is widely used in the quantification of microst...

HybridBranchNetV2: Towards reliable artificial intelligence in image classification using reinforcement learning.

PloS one
Many artificial intelligence (AI) algorithms struggle to adapt effectively in dynamic real-world scenarios, such as complex classification tasks and object relationship extraction, due to their predictable but non-adaptive behavior. This paper introd...

One-shot learning for generalization in medical image classification across modalities.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Generalizability is one of the biggest challenges hindering the advancement of medical sensing technologies across multiple imaging modalities. This issue is further impaired when the imaging data is limited in scope or of poor quality. To tackle thi...

Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model.

Scientific reports
Skin cancer is a prevalent health concern, and accurate segmentation of skin lesions is crucial for early diagnosis. Existing methods for skin lesion segmentation often face trade-offs between efficiency and feature extraction capabilities. This pape...

Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

Scientific reports
To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed...