Nico Curti
University of Bologna
Research areas: Computer Science · Computer Vision and Pattern Recognition · Medical Image Segmentation Techniques · Radiomics and Machine Learning in Medical Imaging · AI in cancer detection
0000-0001-5802-1195
About
Nico Curti was born in Cattolica (RN, Italy) on 28/09/1992.
He obtained the bachelor degree in Physics in 2014 at the University of Bologna (BO, Italy) and the Master Degree in Applied Physics with the vote of 110/110 with laude, defending the work entitled Implementazione e benchmarking dell'algoritmo QDANet PRO per l'analisi di Big Data genomici, developed under the supervision of Prof. Daniel Remondini and Prof. Gastone Castellani.
During his work of thesis, Dr. Nico Curti deepened his informatic skills, focusing his work on the implementation and optimization of algorithms applied on high-performance-computers.
Later, in 2019, he obtained the PhD in Physics, defending the thesis entitled "Implementation and optimization of algorithms in Biological Big Data Analytics" developed under the supervision of Prof. Daniel Remondini, Prof. Gastone Castellani, and Prof. Armando Bazzani at the University of Bologna.
Dr. Curti collaborated with numerous international research groups during his PhD, and he developed applications of data analysis for several academic and private projects.
During the years 2019-2021, Dr. Curti was research fellow at the Dept. of Experimental, Diagnostic and Specialty Medicine of Bologna University, under the supervision of Prof. Enrico Giampieri, Prof. Emanuela Marcelli, and Prof. Gastone Castellani.
Along this period he collaborated to numerous projects about biomedical applications, working side-by-side by expert clinicians.
In particular, he worked on the analysis of histopathological images (WSI) developing machine learning models for the segmentation and characterization of biological tissues and microscopy analyses.
The resulting Decision Support Systems aimed to facilitate and improve the clinical efficiency of the Azienda Ospedaliera IRCCS Sant'Orsola-Malpighi of Bologna.
Furthermore, he collaborated with the Ophatmological Unit of the Azienda Ospedaliera IRCCS Sant'Orsola-Malpighi of Bologna, developing fully automated solutions for the evaluation of slit lamp images.
Dr. Curti worked on several scientific research projects involving the application of artificial intelligence models on radiological images, involving CT, PET, and MRI formats.
The resulting models were used for the automated segmentation of cancer volumes and radiomic analysis of the tissues.
From 2023 to date, Dr. Curti is a junior assistant professor (fixed term) at the Dept. of Physics and Astronomy of Bologna University, under the supervision of Prof. Daniel Remondini.
Employment
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University of Bologna Junior assistant professor (fixed-term)2023 - Present
Education
- 2016 - 2019
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University of Bologna Master Degree2014 - 2016
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University of Bologna Bachelor Degree2011 - 2014
Projects & Funding
Projects & funding information is unavailable.
Publications (44)
- Towards Accurate Breslow Measurements: Mitigating Issues in Histopathological Imaging Save
- Artificial Intelligence–Enhanced MRI Radiomics for Discriminating Active and Fibrotic Lesions to Support Therapeutic Decision Making in Deep Endometriosis Save
- Trichoscopy and Computational Models for Hair and Scalp Disorders: Image Analysis, Quantification, and Clinical Integration Save
- Flow-Based Synthetic Data Generation: A Unified Approach for Biomedical Tasks Save
- Towards Precision Medicine in Sinonasal Tumors: Low-Dimensional Radiomic Signature Extraction from MRI Save
- Emerging Signatures of Hematological Malignancies from Gene Expression and Transcription Factor-Gene Regulations Save
- Artificial Intelligence in Wound Care: A Narrative Review of the Currently Available Mobile Apps for Automatic Ulcer Segmentation Save
- Artificial Intelligence in Wound Care: A Narrative Review of the Currently Available Mobile Apps for Automatic Ulcer Segmentation Save
- Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset Save
- Development and validation of a semi-automated and unsupervised method for femur segmentation from CT Save
- Automated Prediction of Photographic Wound Assessment Tool in Chronic Wound Images Save
- SYNTHETIC DATA GENERATION AND CLASSIFICATION OF HISTOPATHOLOGICAL IMAGES Save
- Automated Wound Image Segmentation: Transfer Learning from Human to Pet via Active Semi-Supervised Learning Save
- Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer Save
- Characterization of Pupillary Light Response Features for the Classification of Patients with Optic Neuritis Save
- Machine Learning Pipeline for the Automated Prediction of MicrovascularInvasion in HepatocellularCarcinomas Save
- Automated Prediction of Photographic Wound Assessment Tool in Chronic Wound Images Save
- Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation Save
- A network approach for low dimensional signatures from high throughput data Save
- Intraspecies characterization of bacteria via evolutionary modeling of protein domains Save