AIMC Topic: Image Processing, Computer-Assisted

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NAVT-net neuron attention visual taylor network for lung cancer detection using CT images.

Computational biology and chemistry
Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Early diagnosis is vital to save the patient's life and Computed Tomography (CT) scans are referred to as the major imaging modes but, the manual examinat...

PMFSNet: Polarized multi-scale feature self-attention network for lightweight medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Current state-of-the-art medical image segmentation methods prioritize precision but often at the expense of increased computational demands and larger model sizes. Applying these large-scale models to the relatively limite...

OCDet: A comprehensive ovarian cell detection model with channel attention on immunohistochemical and morphological pathology images.

Computers in biology and medicine
BACKGROUND: Ovarian cancer is among the most lethal gynecologic malignancy that threatens women's lives. Pathological diagnosis is a key tool for early detection and diagnosis of ovarian cancer, guiding treatment strategies. The evaluation of various...

Risk score stratification of cutaneous melanoma patients based on whole slide images analysis by deep learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: There is a need to improve risk stratification of primary cutaneous melanomas to better guide adjuvant therapy. Taking into account that haematoxylin and eosin (HE)-stained tumour tissue contains a huge amount of clinically unexploited mo...

FDuDoCLNet: Fully dual-domain contrastive learning network for parallel MRI reconstruction.

Magnetic resonance imaging
Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that is widely used for high-resolution imaging of soft tissues and organs. However, the slow speed of MRI imaging, especially in high-resolution or dynamic scans, makes MRI...

Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

Computers in biology and medicine
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmenta...

SEPO-FI: Deep-learning based software to calculate fusion index of muscle cells.

Computers in biology and medicine
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive cou...

Clinically oriented automatic three-dimensional enamel segmentation via deep learning.

BMC oral health
BACKGROUND: Establishing accurate, reliable, and convenient methods for enamel segmentation and analysis is crucial for effectively planning endodontic, orthodontic, and restorative treatments, as well as exploring the evolutionary patterns of mammal...

Performance of the automated digital cell image analyzer UIMD PBIA in white blood cell classification: a comparative study with sysmex DI-60.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aimed to evaluate the performance of PBIA (UIMD, Seoul, Republic of Korea), an automated digital morphology analyzer using deep learning, for white blood cell (WBC) classification in peripheral blood smears and compare it with ...