AIMC Topic: Image Processing, Computer-Assisted

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THERE: Toward an easy and reliable tool for automatic cephalometric analysis.

Computers in biology and medicine
BACKGROUND: Cephalometric analysis in orthodontics is a meticulous process requiring high precision in identifying anatomical landmarks on lateral cephalometric radiographs. Manual analysis by clinicians remains the standard, as even slight deviation...

S2L-CM: Scribble-supervised nuclei segmentation in histopathology images using contrastive regularization and pixel-level multiple instance learning.

Computers in biology and medicine
Deep learning-based pathology nuclei segmentation algorithms have demonstrated remarkable performance. Conventional methods mostly focus on supervised learning, which requires significant manual effort to generate ground truth labels. Recently, weakl...

Advancing label-free cell classification with connectome-inspired explainable models and a novel LIVECell-CLS dataset.

Computers in biology and medicine
Deep learning label-free cell imaging has become essential in modern medical applications, enabling precise cell analysis while preserving natural biological functions and structures by removing the need for potentially disruptive staining reagents. ...

Comparative analysis of deep learning methods for breast ultrasound lesion detection and classification.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Breast ultrasound (BUS) computer-aided diagnosis (CAD) systems aims to perform two major steps: detecting lesions and classifying them as benign or malignant. However, the impact of combining both steps has not been previously addressed. Mor...

AITom: AI-guided cryo-electron tomography image analyses toolkit.

Journal of structural biology
Cryo-electron tomography (cryo-ET) is an essential tool in structural biology, uniquely capable of visualizing three-dimensional macromolecular complexes within their native cellular environments, thereby providing profound molecular-level insights. ...

Local mean suppression filter for effective background identification in fluorescence images.

Computers in biology and medicine
We present an easy-to-use, nonlinear filter for effective background identification in fluorescence microscopy images with dense and low-contrast foreground. The pixel-wise filtering is based on comparison of the pixel intensity with the mean intensi...

Automated whole-breast ultrasound tumor diagnosis using attention-inception network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Automated Whole-Breast Ultrasound (ABUS) has been widely used as an important tool in breast cancer diagnosis due to the ability of this technique to provide complete three-dimensional (3D) images of breasts. To eliminate the risk of misdiag...

Deep-Diffeomorphic Networks for Conditional Brain Templates.

Human brain mapping
Deformable brain templates are an important tool in many neuroimaging analyses. Conditional templates (e.g., age-specific templates) have advantages over single population templates by enabling improved registration accuracy and capturing common proc...

Automated field-in-field planning for tangential breast radiation therapy based on digitally reconstructed radiograph.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: The tangential field-in-field (FIF) technique is a widely used method in breast radiation therapy, known for its efficiency and the reduced number of fields required in treatment planning. However, it is labor-intensive, requiring manual ...

A new diagnostic method and tool for cutaneous leishmaniasis based on artificial intelligence techniques.

Computers in biology and medicine
BACKGROUND: Cutaneous leishmaniasis (CL) is a parasitic disease caused by protozoan parasites of the genus Leishmania, leading to significant morbidity in endemic regions. While effective, traditional diagnostic methods often suffer from limitations ...