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Virtual Expert in the Electron Microscope

Student Project: Virtual Expert in the Electron Microscope   Introduction The 21st century is one of the most productive era in the history of drug discovery. It is largely due to the revolutionized field of structural biology, within which we see the molecule structure, we explore its function, and we design macro molecules to cure […]

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Transfer learning from non-medical datasets

Transfer learning recently became a popular technique for training machine learning algorithms. The goal is to transfer some information from dataset A (the source) to dataset B (the target). This increases the total amount of data the classifier learns from, leading to a more robust algorithm. This is very important for medical imaging datasets, which […]

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Combining relative assessments for melanoma classification

The project addresses melanoma classification in skin lesion images. Typically machine learning algorithms for this application would learn from images which have been labeled as melanoma or not. A less explored option is to learn from relative assessments of images, for example, whether images are similar to each other or not. Such assessments can be […]

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Meta-learning for medical image segmentation

Imagine you have experience with two segmentation applications (for example, tissue segmentation in brain MRI, and cell segmentation in histopathology), and you know that different (deep) learning methods work best in each application. Can you decide which method to use on a third application, for example segmentation of vessels in retinal images, without trying all […]

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Weakly supervised learning in medical imaging (various projects)

Data is often only weakly annotated: for example, for a medical image, we might know the patient’s overall diagnosis, but not where the abnormalities are located, because obtaining ground-truth annotations is very time-consuming. Multiple instance learning (MIL) is an extension of supervised machine learning, aimed at dealing with such weakly labeled data. For example, a […]

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Liver Cancer Recurrence Prediction

The only potentially curative option for patients with colorectal liver metastases (CRLM) or hepatocellular carcinoma (HCC) is surgical resection. However, 80–85% of these patients are not eligible for liver surgery because of extensive intrahepatic metastatic lesions or the presence of extrahepatic disease. Neoadjuvant chemotherapy (NAC) is increasingly applied with the aim to downsize tumors in […]

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Real-time Multimodal Image Registration

Multimodal imaging is increasingly being used within healthcare for diagnosis, planning treatment, guiding treatment, biopsy, surgical navigation and monitoring disease progression. Multimodality imaging takes advantage of the strengths of different imaging modalities to provide a more complete picture of the anatomy under investigation. The goal of this study is to develop a real-time MRI and […]

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Surgical Workflow Analysis

Minimally invasive surgery using cameras to observe the internal anatomy is the preferred approach to many surgical procedures. Furthermore, other surgical disciplines rely on microscopic images. As a result, endoscopic and microscopic image processing, as well as surgical vision, are evolving as techniques needed to facilitate computer-assisted interventions (CAI). Algorithms that have been reported for […]

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