AIMC Topic: Image Processing, Computer-Assisted

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CTCNet: a fine-grained classification network for fluorescence images of circulating tumor cells.

Medical & biological engineering & computing
The identification and categorization of circulating tumor cells (CTCs) in peripheral blood are imperative for advancing cancer diagnostics and prognostics. The intricacy of various CTCs subtypes, coupled with the difficulty in developing exhaustive ...

Automatic skeletal maturity grading from pelvis radiographs by deep learning for adolescent idiopathic scoliosis.

Medical & biological engineering & computing
Adolescent idiopathic scoliosis (AIS) is a three-dimensional spine deformity governed of the spine. A child's Risser stage of skeletal maturity must be carefully considered for AIS evaluation and treatment. However, there are intra-observer and inter...

ShadowGAN-Former: Reweighting self-attention based on mask for shadow removal.

Neural networks : the official journal of the International Neural Network Society
Shadow removal remains a challenging visual task aimed at restoring the original brightness of shadow regions in images. Many existing methods overlook the implicit clues within non-shadow regions, leading to inconsistencies in the color, texture, an...

SAF-IS: A spatial annotation free framework for instance segmentation of surgical tools.

Medical image analysis
Instance segmentation of surgical instruments is a long-standing research problem, crucial for the development of many applications for computer-assisted surgery. This problem is commonly tackled via fully-supervised training of deep learning models,...

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Molecular biology of the cell
Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, hist...

Reinforced Collaborative-Competitive Representation for Biomedical Image Recognition.

Interdisciplinary sciences, computational life sciences
Artificial intelligence technology has demonstrated remarkable diagnostic efficacy in modern biomedical image analysis. However, the practical application of artificial intelligence is significantly limited by the presence of similar pathologies amon...

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Sensors (Basel, Switzerland)
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...

Medical image segmentation based on frequency domain decomposition SVD linear attention.

Scientific reports
Convolutional Neural Networks (CNNs) have achieved remarkable segmentation accuracy in medical image segmentation tasks. However, the Vision Transformer (ViT) model, with its capability of extracting global information, offers a significant advantage...

DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.

Biomedical physics & engineering express
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped n...

Deep proximal gradient network for absorption coefficient recovery in photoacoustic tomography.

Physics in medicine and biology
The optical absorption properties of biological tissues in photoacoustic (PA) tomography are typically quantified by inverting acoustic measurements. Conventional approaches to solving the inverse problem of forward optical models often involve itera...