AIMC Topic: Tomography, X-Ray Computed

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Ultra-High-Resolution Photon-Counting-Detector CT with a Dedicated Denoising Convolutional Neural Network for Enhanced Temporal Bone Imaging.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Ultra-high-resolution (UHR) photon-counting-detector (PCD) CT improves image resolution but increases noise, necessitating the use of smoother reconstruction kernels that reduce resolution below the 0.125-mm maximum spatial re...

SASWISE-UE: Segmentation and synthesis with interpretable scalable ensembles for uncertainty estimation.

Computers in biology and medicine
This paper introduces an efficient sub-model ensemble framework aimed at enhancing the interpretability of medical deep learning models, thus increasing their clinical applicability. By generating uncertainty maps, this framework enables end-users to...

Unsupervised learning-based quantitative analysis of CT intratumoral subregions predicts risk stratification of bladder cancer patients.

BMC medicine
BACKGROUND: Preoperative diagnosis of muscle invasion and American Joint Committee on Cancer (AJCC) stage plays a crucial role in guiding treatment strategies for bladder cancer (BCa). Utilizing quantitative analysis of tumor subregions via CT imagin...

NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.

Journal for immunotherapy of cancer
BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy remains a critical unmet need in resectable non-small-cell lung cancer (NSCLC). Conventional size-base...

Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.

BMC medical imaging
OBJECTIVE: This study aimed to construct a novel model, Multi-Spatial Attention U-Net (MSAU-Net) by incorporating our proposed Multi-Spatial Attention (MSA) block into the U-Net for the automated segmentation of the gallbladder on CT images.

Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees.

Scientific reports
Due to imbalanced data values and high-dimensional features of lung cancer from CT scans images creates significant challenges in clinical research. The improper classification of these images leads towards higher complexity in classification process...

C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion.

Scientific reports
C2 pars interarticularis length (C2PIL) required for pars screws has not been thoroughly studied in subjects with high-riding vertebral artery (HRVA). We aimed to measure C2PIL specifically on the sides with HRVA, define short pars, optimal pars scre...

China Protocol for early screening, precise diagnosis, and individualized treatment of lung cancer.

Signal transduction and targeted therapy
Early screening, diagnosis, and treatment of lung cancer are pivotal in clinical practice since the tumor stage remains the most dominant factor that affects patient survival. Previous initiatives have tried to develop new tools for decision-making o...

Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.

International journal of colorectal disease
PURPOSE: The purpose is to evaluate the predictive value of dual-energy CT (DECT) combined with histogram parameters and a clinical prediction model for perineural invasion (PNI) in colorectal cancer (CRC).