AIMC Topic: Bone Neoplasms
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Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jan 25, 2023
PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often ...
An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.
EBioMedicine
Dec 26, 2022
BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.
Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction.
The American journal of pathology
Dec 21, 2022
Osteosarcoma is the most common primary bone cancer, whose standard treatment includes pre-operative chemotherapy followed by resection. Chemotherapy response is used for prognosis and management of patients. Necrosis is routinely assessed after chem...
Primary bone tumor detection and classification in full-field bone radiographs via YOLO deep learning model.
European radiology
Nov 30, 2022
OBJECTIVES: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model ca...
Bone tumor necrosis rate detection in few-shot X-rays based on deep learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 11, 2022
Although biopsy-based necrosis rate is a golden standard for reflecting the sensitivity of bone tumor and guiding postoperative chemotherapy, it requires biopsy which is invasive and time-consuming. In this paper, we develop a new necrosis rate detec...
Effectiveness of temporal subtraction computed tomography images using deep learning in detecting vertebral bone metastases.
European journal of radiology
Jul 20, 2022
PURPOSE: To assess the clinical effectiveness of temporal subtraction computed tomography (TS CT) using deep learning to improve vertebral bone metastasis detection.
Comparison of skeletal segmentation by deep learning-based and atlas-based segmentation in prostate cancer patients.
Annals of nuclear medicine
Jun 30, 2022
OBJECTIVE: We aimed to compare the deep learning-based (VSBONE BSI) and atlas-based (BONENAVI) segmentation accuracy that have been developed to measure the bone scan index based on skeletal segmentation.
Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer.
Magnetic resonance imaging
Jun 27, 2022
PURPOSE: To assess the possibility of reducing the image acquisition time for diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) by denoising with deep learning-based reconstruction (dDLR).
Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.
Medicina (Kaunas, Lithuania)
May 4, 2022
: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the momen...
Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors.
European radiology
Apr 9, 2022
OBJECTIVES: To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists.
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