body diffusion toolbox postprocessing software (Siemens Healthineers)
90
Structured Review
Siemens Healthineers
body diffusion toolbox postprocessing software
Body Diffusion Toolbox Postprocessing Software, supplied by Siemens Healthineers, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/body+diffusion+toolbox+postprocessing+software/body+diffusion+toolbox/pmc10898033-89-19-24
Average 90 stars, based on 1 article reviews
Body Diffusion Toolbox Postprocessing Software, supplied by Siemens Healthineers, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/body+diffusion+toolbox+postprocessing+software/body+diffusion+toolbox/pmc10898033-89-19-24
Average 90 stars, based on 1 article reviews
body diffusion toolbox postprocessing software - by Bioz Stars,
2026-10
90/100 stars
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Software:Article Title: Predicting disease-free survival in locally advanced rectal cancer using a prognostic model based on pretreatment b-value threshold map and postoperative pathologic features. Article Snippet: Purpose Disease-free survival (DFS) after neoadjuvant chemoradiotherapy (nCRT) is an important factor in affecting the quality of life and determining the subsequent treatment procedures for patients with locally advanced rectal cancer (LARC).. This study aimed to develop a novel prognostic model for predicting the DFS in patients with LARC following nCRT and to verify its effectiveness.. Materials and methods Patients with LARC who underwent magnetic resonance imaging (MRI) and nCRT at our institution between November 2017 and March 2022 were enrolled in this retrospective study. Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy. Article Snippet: .. To obtain IVIM maps, we carried out a pixel-by-pixel fitting of the diffusion-weighted imaging data by using the Article Title: Combined morphology and radiomics of intravoxel incoherent movement as a predictive model for the pathologic complete response before neoadjuvant chemotherapy in patients with breast cancer Article Snippet: .. To obtain IVIM maps, a pixel-by-pixel fitting of DWI data was carried out using a Article Title: Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study Article Snippet: .. From diffusion weighted images with multi-b values, DKI model derived corrected diffusion coefficient (D app ), diffusion kurtosis coefficient (K app ) and conventional diffusion weighted imaging (DWI) derived apparent diffusion coefficient (ADC) were calculated by using the Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy Article Snippet: .. To obtain IVIM maps, we carried out a pixel‐by‐pixel fitting of the diffusion‐weighted imaging data by using the Diffusion-based Assay:Article Title: Predicting disease-free survival in locally advanced rectal cancer using a prognostic model based on pretreatment b-value threshold map and postoperative pathologic features. Article Snippet: Purpose Disease-free survival (DFS) after neoadjuvant chemoradiotherapy (nCRT) is an important factor in affecting the quality of life and determining the subsequent treatment procedures for patients with locally advanced rectal cancer (LARC).. This study aimed to develop a novel prognostic model for predicting the DFS in patients with LARC following nCRT and to verify its effectiveness.. Materials and methods Patients with LARC who underwent magnetic resonance imaging (MRI) and nCRT at our institution between November 2017 and March 2022 were enrolled in this retrospective study. Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy. Article Snippet: .. To obtain IVIM maps, we carried out a pixel-by-pixel fitting of the diffusion-weighted imaging data by using the Article Title: Combined morphology and radiomics of intravoxel incoherent movement as a predictive model for the pathologic complete response before neoadjuvant chemotherapy in patients with breast cancer Article Snippet: .. To obtain IVIM maps, a pixel-by-pixel fitting of DWI data was carried out using a Article Title: Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis. Article Snippet: .. Quantitative MRI Analysis Quantitative analysis included conventional apparent diffusion coefficient (ADC) values derived from the mono-exponential model, as well as Dapp and Kapp values from the DKI model. All DKI images were processed using a workstation ( Article Title: Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis Article Snippet: .. Quantitative analysis included conventional apparent diffusion coefficient (ADC) values derived from the mono-exponential model, as well as D a p p and K a p p values from the DKI model. All DKI images were processed using a workstation ( Article Title: Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study Article Snippet: .. From diffusion weighted images with multi-b values, DKI model derived corrected diffusion coefficient (D app ), diffusion kurtosis coefficient (K app ) and conventional diffusion weighted imaging (DWI) derived apparent diffusion coefficient (ADC) were calculated by using the Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy Article Snippet: .. To obtain IVIM maps, we carried out a pixel‐by‐pixel fitting of the diffusion‐weighted imaging data by using the other:Article Title: ZOOMit diffusion kurtosis imaging combined with diffusion weighted imaging for the assessment of microsatellite instability in endometrial cancer. Article Snippet: 1 Tianjin Medical University Cancer Institute and Hospital, Tianjin, China 2 Xuzhou Maternity and Child Health Care Hospital, Xvzhou, China 3 Siemens Healthcare, Beijing, China Abstract Purpose Detecting microsatellite instability (MSI) plays a key role in the management of endometrial cancer (EC), as it is a critical predictive biomarker for Lynch syndrome or immunotherapy response.. A pressing need exists for cost-efficient, broadly accessible tools to aid patient for universal testing.. Herein, we investigate the value of ZOOMit diffusion kurtosis imaging (DKI) and diffusion weighted imaging (DWI) based on preoperative pelvic magnetic resonance imaging (MRI) images in assessing MSI in EC. Imaging:Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy. Article Snippet: .. To obtain IVIM maps, we carried out a pixel-by-pixel fitting of the diffusion-weighted imaging data by using the Article Title: Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study Article Snippet: .. From diffusion weighted images with multi-b values, DKI model derived corrected diffusion coefficient (D app ), diffusion kurtosis coefficient (K app ) and conventional diffusion weighted imaging (DWI) derived apparent diffusion coefficient (ADC) were calculated by using the Article Title: Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy Article Snippet: .. To obtain IVIM maps, we carried out a pixel‐by‐pixel fitting of the diffusion‐weighted imaging data by using the Magnetic Resonance Imaging:Article Title: Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis. Article Snippet: .. Quantitative MRI Analysis Quantitative analysis included conventional apparent diffusion coefficient (ADC) values derived from the mono-exponential model, as well as Dapp and Kapp values from the DKI model. All DKI images were processed using a workstation ( Derivative Assay:Article Title: Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis. Article Snippet: .. Quantitative MRI Analysis Quantitative analysis included conventional apparent diffusion coefficient (ADC) values derived from the mono-exponential model, as well as Dapp and Kapp values from the DKI model. All DKI images were processed using a workstation ( Article Title: Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis Article Snippet: .. Quantitative analysis included conventional apparent diffusion coefficient (ADC) values derived from the mono-exponential model, as well as D a p p and K a p p values from the DKI model. All DKI images were processed using a workstation ( Article Title: Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study Article Snippet: .. From diffusion weighted images with multi-b values, DKI model derived corrected diffusion coefficient (D app ), diffusion kurtosis coefficient (K app ) and conventional diffusion weighted imaging (DWI) derived apparent diffusion coefficient (ADC) were calculated by using the |