Roger Trullo
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View article: Cross-species efficacy of AAV-mediated ARSA replacement for metachromatic leukodystrophy
Cross-species efficacy of AAV-mediated ARSA replacement for metachromatic leukodystrophy Open
Metachromatic leukodystrophy (MLD) is an autosomal recessive neurodegenerative disorder caused by mutations in the arylsulfatase A (ARSA) gene, resulting in lower sulfatase activity and the toxic accumulation of sulfatides in the central a…
View article: MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models
MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models Open
Histopathological analysis is a cornerstone of cancer diagnosis, with Hematoxylin and Eosin (H&E) staining routinely acquired for every patient to visualize cell morphology and tissue architecture. On the other hand, multiplex immunofluore…
View article: AAV-mediated ARSA replacement for the treatment of Metachromatic Leukodystrophy
AAV-mediated ARSA replacement for the treatment of Metachromatic Leukodystrophy Open
Metachromatic leukodystrophy (MLD) is an autosomal recessive neurodegenerative disorder caused by mutations in the arylsulfatase A (ARSA) gene, resulting in lower sulfatase activity and the toxic accumulation of sulfatides in the central a…
View article: Medical Image Synthesis with Deep Convolutional Adversarial Networks
Medical Image Synthesis with Deep Convolutional Adversarial Networks Open
Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and radiation dose, the acquisition of certain image modalities may be limited. Thus, medical image synthesis can …
View article: Classification of the Tumor Immune Microenvironment Using Machine-Learning-Based CD8 Immunophenotyping As a Potential Biomarker for Immunotherapy and TGF-β Blockade in Nonsmall Cell Lung Cancer
Classification of the Tumor Immune Microenvironment Using Machine-Learning-Based CD8 Immunophenotyping As a Potential Biomarker for Immunotherapy and TGF-β Blockade in Nonsmall Cell Lung Cancer Open
Background: The cellular composition of the tumor immune microenvironment (TIME) is a key contributor to the response of the tumor to immunotherapy. Transforming growth factor-beta (TGF-β) signaling is known to promote immune exclusion, wh…
View article: P487 Automated Scoring of Patient Endoscopy Videos Using Deep Learning Techniques: A Promising Approach for Clinical Trials in Inflammatory Bowel Disease
P487 Automated Scoring of Patient Endoscopy Videos Using Deep Learning Techniques: A Promising Approach for Clinical Trials in Inflammatory Bowel Disease Open
Background Accurate assessment of patient endoscopy videos is crucial for various clinical trials, including those related to inflammatory bowel diseases (IBD). However, manual scoring by trained local and central readers can lead to discr…
View article: RoFormer for Position Aware Multiple Instance Learning in Whole Slide Image Classification
RoFormer for Position Aware Multiple Instance Learning in Whole Slide Image Classification Open
Whole slide image (WSI) classification is a critical task in computational pathology. However, the gigapixel-size of such images remains a major challenge for the current state of deep-learning. Current methods rely on multiple-instance le…
View article: Image Translation Based Nuclei Segmentation for Immunohistochemistry Images
Image Translation Based Nuclei Segmentation for Immunohistochemistry Images Open
Numerous deep learning based methods have been developed for nuclei segmentation for H&E images and have achieved close to human performance. However, direct application of such methods to another modality of images, such as Immunohistoche…
View article: Corrections to “Medical Image Synthesis With Deep Convolutional Adversarial Networks” [Mar 18 2720-2730]
Corrections to “Medical Image Synthesis With Deep Convolutional Adversarial Networks” [Mar 18 2720-2730] Open
Presents corrections to grant and sponsorship information in the above named paper.
View article: Medical Image Synthesis with Deep Convolutional Adversarial Networks
Medical Image Synthesis with Deep Convolutional Adversarial Networks Open
Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and radiation dose, the acquisition of certain image modalities may be limited. Thus, medical image synthesis can …
View article: Fully automated esophagus segmentation with a hierarchical deep learning approach
Fully automated esophagus segmentation with a hierarchical deep learning approach Open
Segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper we focus on esophagus segmentation, a challenging problem since the walls of the esophagus have a very low contrast in CT ima…
View article: Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields
Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields Open
Cancer is one of the leading causes of death worldwide. Radiotherapy is a standard treatment for this condition and the first step of the radiotherapy process is to identify the target volumes to be targeted and the healthy organs at risk …
View article: Medical Image Synthesis with Context-Aware Generative Adversarial Networks
Medical Image Synthesis with Context-Aware Generative Adversarial Networks Open
Computed tomography (CT) is critical for various clinical applications, e.g., radiotherapy treatment planning and also PET attenuation correction. However, CT exposes radiation during acquisition, which may cause side effects to patients. …