AIMC Topic: Tomography, X-Ray Computed

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Machine learning-based prediction of N2 lymph node metastasis in non-small cell lung cancer.

BMC pulmonary medicine
BACKGROUND: Lung cancer is a leading cause of cancer-related mortality worldwide. Accurate staging of mediastinal lymph nodes is a crucial step in determining appropriate treatment approaches. Current noninvasive diagnostic methods do not provide suf...

Predicting hematologic toxicity in advanced cervical cancer patients using interpretable machine learning models based on radiomics and dosimetrics.

BMC cancer
BACKGROUND AND OBJECTIVES: Hematologic toxicity (HT) is a common and serious side effect for advanced cervical cancer patients undergoing chemoradiotherapy. Accurately predicting HT can significantly improve patient management and treatment outcomes....

Insertion of hepatic lesions into clinical photon-counting-detector CT projection data.

Physics in medicine and biology
To facilitate task-driven image quality assessment of lesion detectability in clinical photon-counting-detector CT (PCD-CT), it is desired to have patient image data with known pathology and precise annotation. Standard patient case collection and re...

Exploiting deep transfer learning based precise classification and grading of renal cell carcinoma using histopathological images.

Scientific reports
Renal cancer is a key reason for cancer-related deaths among males worldwide. Earlier diagnosis of renal cancer is critical since it can considerably increase the chance of survivability. However evaluating the histopathological renal tissue is a ted...

YOLOv12 Algorithm-Aided Detection and Classification of Lateral Malleolar Avulsion Fracture and Subfibular Ossicle Based on CT Images: Multicenter Study.

JMIR medical informatics
BACKGROUND: Lateral malleolar avulsion fractures (LMAFs) and subfibular ossicles (SFOs) are distinct entities that both present as small bone fragments near the lateral malleolus in imaging but require different treatment strategies. Clinical and rad...

Automated contouring of gross tumor volume lymph nodes in lung cancer by deep learning.

BMC cancer
PURPOSE: The precise contouring of gross tumor volume lymph nodes (GTVnd) is an essential step in clinical target volume delineation. This study aims to propose and evaluate a deep learning model for segmenting GTVnd specifically in lung cancer, repr...

Deep transfer learning based feature fusion model with Bonobo optimization algorithm for enhanced brain tumor segmentation and classification through biomedical imaging.

Scientific reports
The brain tumour (BT) is an aggressive disease among others, which leads to a very short life expectancy. Therefore, early and prompt treatment is the main stage in enhancing patients' quality of life. Biomedical imaging permits the non-invasive eval...

Radiomics-enhanced modelling approach for predicting the need for ECMO in ARDS patients: a retrospective cohort study.

Scientific reports
Decisions regarding veno-venous extracorporeal membrane oxygenation (vv-ECMO) in patients with acute respiratory distress syndrome (ARDS) are often based solely on clinical and physiological parameters, which may insufficiently reflect severity and h...

A phase-aware Cross-Scale U-MAMba with uncertainty-aware segmentation and Switch Atrous Bifovea EfficientNetB7 classification of kidney lesion subtype.

Lasers in medical science
Kidney lesion subtype identification is essential for precise diagnosis and personalized treatment planning. However, achieving reliable classification remains challenging due to factors such as inter-patient anatomical variability, incomplete multi-...

Mixed prototype correction for causal inference in medical image classification.

Scientific reports
The heterogeneity of medical images poses significant challenges to accurate disease diagnosis. To tackle this issue, the impact of such heterogeneity on the causal relationship between image features and diagnostic labels should be incorporated into...