Categories: Research with mint

Doctors looking at MRI scans to evaluate a glioblastoma.

Optimizing Glioblastoma Imaging: Enhancing MRI Efficiency and Quality with Deep Learning

This study investigates the use of deep learning (DL) to optimize MRI protocols for glioblastoma patients, aiming to reduce scan time and improve…

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Three important sequences (FLAIR, T2, T1 with contrast agent) in the assessment of glioblastoma

University Hospital Tübingen: Advancing MRI Efficiency in Glioblastoma Care with Deep Learning

This study explores the use of deep learning (DL) to optimize MRI protocols for glioblastoma patients. Glioblastomas, known for being the most…

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mint Lesion screenshot with HCC diagnosis according to APASL, AASLD, LI-RADS, KLCA-NCC, and EASL guidelines

Seoul National University Hospital: Comparison of Diagnostic Guidelines for Hepatocellular Carcinoma

Recent advancements in MRI techniques and tumor biology have led to updated hepatocellular carcinoma (HCC) diagnostic guidelines from various liver…

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Schematic visualization of the federated learning study and its data infrastructure

RACOON: A Guide to Bridging the Gap Between Simulated and Real-World Federated Learning Research

Deep learning (DL) has become an important part of radiological image analysis. To train these deep-learning models, access to large and diverse…

Data Collection AI Research with mint
Picture shows a scan of pericardial effusion

RACOON: Study emphasizes the clinical relevance of pericardial effusion as an imaging biomarker in COVID-19 patients

A multicenter study [1] based on the German research infrastructure project RACOON (Radiological Cooperative Network of the COVID-19 pandemic; a Netzw…

RACOON Interoperability Standardized Reading Procedures COVID-19 Research with mint
Diagram that shows reduced reading times for the mint Lesion™ approach at both follow-ups.

UKE Hamburg: Study Shows that Software-Assisted Assessments Enhance iRECIST Evaluation

This research study [1] aimed to compare the feasibility and reliability of manual versus software-assisted assessments of computed tomography (CT)…

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mint Lesion screenshot with segmented muscles and radiomics

University Hospital Ulm: CT Radiomics and Machine Learning in Sarcopenia Evaluation for Esophageal and Gastric Cancer Patients

A recent study [1] conducted by researchers at University Hospital Ulm explored the role of sarcopenia in patients with esophageal or gastric cancer.…

Radiomics Research with mint
Several juxtaposed images of different patients with different responses to the cancer treatment

Study with mint Lesion™ compares the Efficacy of SIRT and CS-PHP in Uveal Melanoma with Hepatic Metastasis

A study conducted by researchers at University Hospital Tuebingen retrospectively compared two liver-targeted therapies for uveal melanoma patients…

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RECIST measurements of a patient with uveal melanoma and hepatic metastases

University Hospital Tuebingen: Study compares the Efficacy of SIRT and CS-PHP in Uveal Melanoma with Hepatic Metastasis

A study[1] conducted by researchers at University Hospital Tuebingen retrospectively compared the efficacy of two liver-targeted therapies,…

Structured Reporting Clinical Trials Clinical Research Standardized Reading Procedures Therapy Response Assessment Research with mint