AIMC Topic: Tomography, X-Ray Computed

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Points of interest linear attention network for real-time non-rigid liver volume to surface registration.

Medical physics
BACKGROUND: In laparoscopic liver surgery, accurately predicting the displacement of key intrahepatic anatomical structures is crucial for informing the doctor's intraoperative decision-making. However, due to the constrained surgical perspective, on...

[New Method of Paired Comparison for Improved Observer Shortage Using Deep Learning Models].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The aim of this study was to validate the potential of substituting an observer in a paired comparison with a deep-learning observer.

Automated Analysis of Split Kidney Function from CT Scans Using Deep Learning and Delta Radiomics.

Journal of endourology
Differential kidney function assessment is an important part of preoperative evaluation of various urological interventions. It is obtained through dedicated nuclear medical imaging and is not yet implemented through conventional Imaging. We assess...

Automatic segmentation of femoral tumors by nnU-net.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Metastatic femoral tumors may lead to pathological fractures during daily activities. A CT-based finite element analysis of a patient's femurs was shown to assist orthopedic surgeons in making informed decisions about the risk of fracture...

A multi-view fusion lightweight network for CRSwNPs prediction on CT images.

BMC medical imaging
Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS (non-eCRS) is an important topic in predicting postoperative outcomes and administering personalized treatment...

Patient classification and attribute assessment based on machine learning techniques in the qualification process for surgical treatment of adrenal tumours.

Scientific reports
Adrenal gland incidentaloma is frequently identified through computed tomography and poses a common clinical challenge. Only selected cases require surgical intervention. The primary aim of this study was to compare the effectiveness of selected mach...

Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.

PloS one
The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. Howev...