PACHETTI, EVA
PACHETTI, EVA
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Boosting few-shot learning with disentangled self-supervised learning and meta-learning for medical image classification
In corso di stampa Pachetti, E.; Tsaftaris, S. A.; Colantonio, S.
A systematic review of few-shot learning in medical imaging
2024 Pachetti, E; Colantonio, S
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement
2024 Xue, Y; Du, Y; Carloni, G; Pachetti, E; Jordan, C; Tsaftaris, Sa
Few-shot conditional learning: automatic and reliable device classification for medical test equipment
2024 Pachetti, E.; Del Corso, G.; Bardelli, S.; Colantonio, S.
From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment
2024 Berti, A.; Buongiorno, R.; Carloni, G.; Caudai, C.; Conti, F.; Del Corso, G.; Germanese, D.; Moroni, D.; Pachetti, E.; Pascali, M. A.; Colantonio, S.
Hallucinating for diagnosing: one-shot medical image classification leveraging score-based generative models
2024 Pachetti, E.; Colantonio, S.
Radiomics-based reliable predictions of side effects after radiotherapy for prostate cancer
2024 Del Corso, G.; Pachetti, E.; Buongiorno, R.; Rodrigues, A. C.; Germanese, D.; Pascali, M. A.; Almeida, J.; Rodrigues, N.; Tsiknakis, M.; Papanikolaou, N.; Regge, D.; Marias, K.; Consortium, ProCAncer-I; Colantonio, S.
3D-Vision-transformer stacking ensemble for assessing prostate cancer aggressiveness from T2w images
2023 Pachetti, E; Colantonio, S
AI trustworthiness in prostate cancer imaging: a look at algorithmic and system transparency
2023 Colantonio, S; Berti, A; Buongiorno, R; Del Corso, G; Pachetti, E; Pascali, Ma; Kalantzopoulos, C; Kalokyri, V; Kondylakis, H; Tachos, N; Fotiadis, D; Giannini, V; Mazzetti, S; Regge, D; Papanikolaou, N; Marias, K; Tsiknakis, M
Causality-driven one-shot learning for prostate cancer grading from MRI
2023 Carloni, G; Pachetti, E; Colantonio, S
Exploring the potentials and challenges of AI in supporting clinical diagnostics and remote assistance for the health and well-being of individuals
2023 Berti A.; Buongiorno R.; Carloni G.; Caudai C.; Del Corso G.; Germanese D.; Pachetti E.; Pascali M.A.; Colantonio S.
Exploring the potentials and challenges of Artificial Intelligence in supporting clinical diagnostics and remote assistance for the health and well-being of individuals
2023 Berti, A.; Buongiorno, R.; Carloni, G.; Caudai, C.; Del Corso, G.; Germanese, D.; Pachetti, E.; Pascali, M. A.; Colantonio, S.
Data models for an imaging bio-bank for colorectal, prostate and gastric cancer: the NAVIGATOR project
2022 Berti, A; Carloni, G; Colantonio, S; Pascali, Ma; Manghi, P; Pagano, P; Buongiorno, R; Pachetti, E; Caudai, C; Di Gangi, D; Carlini, E; Falaschi, Z; Ciarrocchi, E; Neri, E; Bertelli, E; Miele, V; Carpi, R; Bagnacci, G; Di Meglio, N; Mazzei, Ma; Barucci, A
Machine and deep learning prediction of prostate cancer aggressiveness using multiparametric MRI
2022 Bertelli, E; Mercatelli, L; Marzi, C; Pachetti, E; Baccini, M; Barucci, A; Colantonio, S; Gherardini, L; Lattavo, L; Pascali, Ma; Agostini, S; Miele, V
On the effectiveness of 3D vision transformers for the prediction of prostate cancer aggressiveness
2022 Pachetti E.; Colantonio S.; Pascali M.A.
SI-Lab annual research report 2021
2022 Righi, M; Leone, GIUSEPPE RICCARDO; Carboni, A; Caudai, C; Colantonio, S; Kuruoglu, ERCAN ENGIN; Leporini, B; Magrini, M; Paradisi, P; Pascali, MARIA ANTONIETTA; Pieri, G; Reggiannini, M; Salerno, E; Scozzari, A; Tonazzini, A; Fusco, G; Galesi, G; Martinelli, M; Pardini, F; Tampucci, M; Berti, A; Bruno, A; Buongiorno, R; Carloni, G; Conti, F; Germanese, D; Ignesti, G; Matarese, F; Omrani, A; Pachetti, E; Papini, O; Benassi, A; Bertini, G; Coltelli, P; Tarabella, L; Straface, S; Salvetti, O; Moroni, D
Technical report on the development and interpretation of convolutional neural networks for the classification of multiparametric MRI images on unbalanced datasets. Case study: prostate cancer
2021 Pachetti, E; Colantonio, S
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Boosting few-shot learning with disentangled self-supervised learning and meta-learning for medical image classification | In corso di stampa | Pachetti, E.; Tsaftaris, S. A.; Colantonio, S. | |
| A systematic review of few-shot learning in medical imaging | 1-gen-2024 | Pachetti, E; Colantonio, S | |
| Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement | 1-gen-2024 | Xue, Y; Du, Y; Carloni, G; Pachetti, E; Jordan, C; Tsaftaris, Sa | |
| Few-shot conditional learning: automatic and reliable device classification for medical test equipment | 1-gen-2024 | Pachetti, E.; Del Corso, G.; Bardelli, S.; Colantonio, S. | |
| From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment | 1-gen-2024 | Berti, A.; Buongiorno, R.; Carloni, G.; Caudai, C.; Conti, F.; Del Corso, G.; Germanese, D.; Moroni, D.; Pachetti, E.; Pascali, M. A.; Colantonio, S. | |
| Hallucinating for diagnosing: one-shot medical image classification leveraging score-based generative models | 1-gen-2024 | Pachetti, E.; Colantonio, S. | |
| Radiomics-based reliable predictions of side effects after radiotherapy for prostate cancer | 1-gen-2024 | Del Corso, G.; Pachetti, E.; Buongiorno, R.; Rodrigues, A. C.; Germanese, D.; Pascali, M. A.; Almeida, J.; Rodrigues, N.; Tsiknakis, M.; Papanikolaou, N.; Regge, D.; Marias, K.; Consortium, ProCAncer-I; Colantonio, S. | |
| 3D-Vision-transformer stacking ensemble for assessing prostate cancer aggressiveness from T2w images | 1-gen-2023 | Pachetti, E; Colantonio, S | |
| AI trustworthiness in prostate cancer imaging: a look at algorithmic and system transparency | 1-gen-2023 | Colantonio, S; Berti, A; Buongiorno, R; Del Corso, G; Pachetti, E; Pascali, Ma; Kalantzopoulos, C; Kalokyri, V; Kondylakis, H; Tachos, N; Fotiadis, D; Giannini, V; Mazzetti, S; Regge, D; Papanikolaou, N; Marias, K; Tsiknakis, M | |
| Causality-driven one-shot learning for prostate cancer grading from MRI | 1-gen-2023 | Carloni, G; Pachetti, E; Colantonio, S | |
| Exploring the potentials and challenges of AI in supporting clinical diagnostics and remote assistance for the health and well-being of individuals | 1-gen-2023 | Berti A.; Buongiorno R.; Carloni G.; Caudai C.; Del Corso G.; Germanese D.; Pachetti E.; Pascali M.A.; Colantonio S. | |
| Exploring the potentials and challenges of Artificial Intelligence in supporting clinical diagnostics and remote assistance for the health and well-being of individuals | 1-gen-2023 | Berti, A.; Buongiorno, R.; Carloni, G.; Caudai, C.; Del Corso, G.; Germanese, D.; Pachetti, E.; Pascali, M. A.; Colantonio, S. | |
| Data models for an imaging bio-bank for colorectal, prostate and gastric cancer: the NAVIGATOR project | 1-gen-2022 | Berti, A; Carloni, G; Colantonio, S; Pascali, Ma; Manghi, P; Pagano, P; Buongiorno, R; Pachetti, E; Caudai, C; Di Gangi, D; Carlini, E; Falaschi, Z; Ciarrocchi, E; Neri, E; Bertelli, E; Miele, V; Carpi, R; Bagnacci, G; Di Meglio, N; Mazzei, Ma; Barucci, A | |
| Machine and deep learning prediction of prostate cancer aggressiveness using multiparametric MRI | 1-gen-2022 | Bertelli, E; Mercatelli, L; Marzi, C; Pachetti, E; Baccini, M; Barucci, A; Colantonio, S; Gherardini, L; Lattavo, L; Pascali, Ma; Agostini, S; Miele, V | |
| On the effectiveness of 3D vision transformers for the prediction of prostate cancer aggressiveness | 1-gen-2022 | Pachetti E.; Colantonio S.; Pascali M.A. | |
| SI-Lab annual research report 2021 | 1-gen-2022 | Righi, M; Leone, GIUSEPPE RICCARDO; Carboni, A; Caudai, C; Colantonio, S; Kuruoglu, ERCAN ENGIN; Leporini, B; Magrini, M; Paradisi, P; Pascali, MARIA ANTONIETTA; Pieri, G; Reggiannini, M; Salerno, E; Scozzari, A; Tonazzini, A; Fusco, G; Galesi, G; Martinelli, M; Pardini, F; Tampucci, M; Berti, A; Bruno, A; Buongiorno, R; Carloni, G; Conti, F; Germanese, D; Ignesti, G; Matarese, F; Omrani, A; Pachetti, E; Papini, O; Benassi, A; Bertini, G; Coltelli, P; Tarabella, L; Straface, S; Salvetti, O; Moroni, D | |
| Technical report on the development and interpretation of convolutional neural networks for the classification of multiparametric MRI images on unbalanced datasets. Case study: prostate cancer | 1-gen-2021 | Pachetti, E; Colantonio, S |