1.

Record Nr.

UNINA9910983086703321

Autore

Mann Ritse M

Titolo

Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care : First Deep Breast Workshop, Deep-Breath 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings / / edited by Ritse M. Mann, Tianyu Zhang, Tao Tan, Luyi Han, Danial Truhn, Shuo Li, Yuan Gao, Shannon Doyle, Robert Martí Marly, Jakob Nikolas Kather, Katja Pinker-Domenig, Shandong Wu, Geert Litjens

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025

ISBN

9783031777899

3031777891

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (405 pages)

Collana

Lecture Notes in Computer Science, , 1611-3349 ; ; 15451

Altri autori (Persone)

ZhangTianyu

TanTao

HanLuyi

TruhnDanial

LiShuo

GaoYuan

DoyleShannon

Martí MarlyRobert

KatherJakob Nikolas

Disciplina

006.3

Soggetti

Artificial intelligence

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Evaluation of Bagging Ensembles on Multimodal Data for Breast Cancer Diagnosis -- HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging -- DuEU-Net: Dual Encoder UNet with Modality-Agnostic Training for PET-CT Multi-Modal Organ and Lesion Segmentation -- One for All: UNET Training on Single-Sequence Masks for Multi-Sequence Breast MRI Segmentation -- Multimodal Breast MRI Language-Image Pretraining (MLIP): An



Exploration of a Breast MRI Foundation Model -- Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data -- Efficient Generation of Synthetic Breast CT Slices By Combining Generative and Super-Resolution Models -- Exploring Patient Data Requirements in Training Effective AI Models for MRI-based Breast Cancer Classification -- Virtual dynamic contrast enhanced breast MRI using 2D U-Net -- Optimizing BI-RADS 4 Lesion Assessment using Lightweight Convolutional Neural Network with CBAM in Contrast Enhanced Mammography -- Mammographic Breast Positioning Assessment via Deep Learning -- Endpoint Detection in Breast Images for Automatic Classification of Breast Cancer Aesthetic Results -- Thick Slices for Optimal Digital Breast Tomosynthesis Classification with Deep-Learning -- Predicting Aesthetic Outcomes in Breast Cancer Surgery: a Multimodal Retrieval Approach -- Vision Mamba for Classification of Breast Ultrasound Images -- Breast Cancer Molecular Subtyping from H&E Whole Slide Images using Foundation Models and Transformers -- Graph Neural Networks for modelling breast biomechanical compression -- A generative adversarial approach to remove Moiré artifacts in Dark-field and Phase-contrast x-ray images -- MRI Breast tissue segmentation using nnUNet for Biomechanical modeling -- Fat-Suppressed Breast MRI Synthesis for Domain Adaptation in Tumour Segmentation -- Guiding Breast Conservative Surgery by Augmented Reality from Preoperative MRI: Initial System Design and Retrospective Trials -- ELK: Enhanced Learning through cross-modal Knowledge transfer for lesion detection in limited-sample contrast-enhanced mammography datasets -- Safe Breast Cancer Diagnosis Resilient to Mammographic Adversarial Samples.

Sommario/riassunto

This book constitutes the refereed proceedings of the First Deep Breast Workshop on Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care, Deep-Breath 2024, held in conjunction with the 26th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 10, 2024.The 23 regular papers presented in this book were carefully reviewed and selected from 51 submissions.The workshop provides an international platform for presentation of - and discussion on - studies related to AI in breast imaging. Deep-Breath aims to promote the development of this research area by sharing insights in academic research and clinical practice between clinicians and AI experts, and by exploring together the opportunities and potential challenges of AI applications in breast health. The deep-breath workshop provides, therefore, an unique forum to discuss the possibilities in this challenging field, aiming to create value that eventually truly leads to benefit for physicians and patients.



2.

Record Nr.

UNINA9910965234903321

Autore

Denning Stephen

Titolo

The secret language of leadership : how leaders inspire action through narrative / / Stephen Denning

Pubbl/distr/stampa

San Francisco, : Jossey-Bass, c2007

ISBN

9786611032548

9780470493250

0470493259

9781118047378

1118047370

9781281032546

1281032549

9780470184400

047018440X

Edizione

[1st ed.]

Descrizione fisica

1 online resource (305 p.)

Collana

J-B US non-Franchise Leadership ; ; v.40

Disciplina

658.4/5

Soggetti

Leadership

Communication in organizations

Storytelling

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. 245-263) and index.

Nota di contenuto

What is transformational leadership? -- Introduction: Ten mistakes transformational leaders make -- The secret language of leadership -- The language of leadership: key enablers -- Articulating a clear, inspiring goal -- The leader's own story: committing to the goal -- Mastering the audience's story -- Cultivating narrative intelligence -- Telling truthful stories -- Leadership presence: the body language of leadership -- The language of leadership: key steps -- Getting people's attention -- Stimulating desire -- Reinforcing with reason -- Continuing the conversation -- Epilogue.

Sommario/riassunto

The book introduces the concept of narrative intelligence-an ability to understand and act and react agilely in the quicksilver world of interacting narratives. It shows why this is key to the central task of



leadership, what its dimensions are, and how you can measure it. The book's lucid explanations, vivid examples and practical tips are essential reading for CEOs, managers, change agents, marketers, salespersons, brand managers, politicians, teachers, parents-anyone who is setting out to the change the world.

3.

Record Nr.

UNINA9910893936603321

Titolo

Architektonische Studien

Pubbl/distr/stampa

Stuttgart, : Universitätsbibliothek, 2018

Descrizione fisica

Online-Ressource

Disciplina

690

Soggetti

Architektur

Grundriss

Architekturzeichnung

Beispielsammlung

Zeitschrift

Lingua di pubblicazione

Tedesco

Formato

Materiale a stampa

Livello bibliografico

Periodico

Note generali

Reproduktion