AIMC Topic: Image Processing, Computer-Assisted

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Self-Supervised Multimodal Learning: A Survey.

IEEE transactions on pattern analysis and machine intelligence
Multimodal learning, which aims to understand and analyze information from multiple modalities, has achieved substantial progress in the supervised regime in recent years. However, the heavy dependence on data paired with expensive human annotations ...

Journey from image acquisition to biological insight: handling and analyzing large volumes of light-sheet imaging data.

Microscopy (Oxford, England)
Recent advancements in imaging technologies have enabled the acquisition of high-quality, voluminous, multidimensional image data. Among these, light-sheet microscopy stands out for its ability to capture dynamic biological processes over extended pe...

A guide to CNN-based dense segmentation of neuronal EM images.

Microscopy (Oxford, England)
Large-scale reconstitution of neuronal circuits from volumetric electron microscopy images is a remarkable research goal in neuroanatomy. However, the large-scale reconstruction is a result of automatic segmentation using convolutional neural network...

[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other medical fields. However, repeated CBCT scans expose patients to additional radiation doses, increasing the risk of secondary malignant tumors. Low-dose ...

[Cross modal translation of magnetic resonance imaging and computed tomography images based on diffusion generative adversarial networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
To address the issues of difficulty in preserving anatomical structures, low realism of generated images, and loss of high-frequency image information in medical image cross-modal translation, this paper proposes a medical image cross-modal translati...

Think deep in the tractography game: deep learning for tractography computing and analysis.

Brain structure & function
Tractography is a challenging process with complex rules, driving continuous algorithmic evolution to address its challenges. Meanwhile, deep learning has tackled similarly difficult tasks, such as mastering the Go board game and animating sophistica...

OCT in dermatology: a process for determining whether a fully diversified dataset is needed for AI model-building.

Optics letters
Optical coherence tomography (OCT) has sufficient depth penetration for detection of skin pathologies, but its detection effectiveness can be aided by the assistance of artificial intelligence (AI) modeling. AI model-building identifies pathologies b...

Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.

Biomedical physics & engineering express
: Effective lung gas exchange relies on the balance between alveolar ventilation and perfusion, which can be disrupted in mechanically ventilated patients. Lung perfusion assessment using electrical impedance tomography (EIT) typically involves a sud...