AIMC Topic: Necrosis
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A preoperative CT-based deep learning radiomics model in predicting the stage, size, grade and necrosis score and outcome in localized clear cell renal cell carcinoma: A multicenter study.
European journal of radiology
Jul 29, 2023
BACKGROUND AND PURPOSE: The Stage, Size, Grade and Necrosis (SSIGN) score is the most commonly used prognostic model in clear cell renal cell carcinoma (ccRCC) patients. It is a great challenge to preoperatively predict SSIGN score and outcome of ccR...
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...
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...
Effect of process parameters on the temperature changes during robotic bone drilling.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Jul 12, 2022
In medical surgery, bone drilling is an inevitable procedure. The thermal necrosis in the drilling process can affect post-operative recovery. In this study, the method of drill bit precooling is proposed in bone drilling with robot assisted system. ...
Deep learning for necrosis detection using canine perivascular wall tumour whole slide images.
Scientific reports
Jun 23, 2022
Necrosis seen in histopathology Whole Slide Images is a major criterion that contributes towards scoring tumour grade which then determines treatment options. However conventional manual assessment suffers from inter-operator reproducibility impactin...
Early prediction of acute necrotizing pancreatitis by artificial intelligence: a prospective cohort-analysis of 2387 cases.
Scientific reports
May 12, 2022
Pancreatic necrosis is a consistent prognostic factor in acute pancreatitis (AP). However, the clinical scores currently in use are either too complicated or require data that are unavailable on admission or lack sufficient predictive value. We there...
Computer-Generated R.E.N.A.L. Nephrometry Scores Yield Comparable Predictive Results to Those of Human-Expert Scores in Predicting Oncologic and Perioperative Outcomes.
The Journal of urology
Dec 30, 2021
PURPOSE: We sought to automate R.E.N.A.L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry scoring of preoperative computerized tomography scans and create an ...
Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.
PloS one
Sep 15, 2020
The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live a...
Machine Learning to Quantitate Neutrophil NETosis.
Scientific reports
Nov 15, 2019
We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate...
Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.
International journal of computer assisted radiology and surgery
Apr 30, 2019
PURPOSE: We address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcinoma (HCC) tumor) on multiphase CT images using a deep learning approach.
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