Methods for 3D reconstructions in dermoscopy

In the iToBoS project, the so-called 3D cameras are used. These cameras enable us to make a virtual representation of the patient. This can help the dermatologists to match dermoscopic images of lesions with the lesions on the body of the patient.

Classification system for skin lesions, the more detailed the better

Skin cancer is one of the most common cancers in the world. Late-stage skin cancers spreads to internal organs and become fatal. Early-stage skin cancer can be cured with a high survival rate, while the 5-year survival rate for skin cancer is extremely low. Therefore, early detection is the key in fighting skin cancer.

[GR] iToBoS – Ευφυής Σαρωτής Ολόκληρου του Δώματος για την Έγκαιρη Διάγνωση Μελανώματος

Το iToBoS είναι ένα ερευνητικό έργο που χρηματοδοτείται από το πρόγραμμα έρευνας και καινοτομίας της Ευρωπαϊκής Επιτροπής Horizon 2020, στο θέμα "Ψηφιακή διαγνωστική - Ανάπτυξη εργαλείων για την υποστήριξη κλινικών αποφάσεων ενσωματώνοντας διάφορα είδη διαγνωστικών δεδομένων".

Skin cancers: data and facts

The most updated source for worldwide cancer data is represented by the GLOBOCAN 2020 report of the International Agency of Cancer Research (IACR).

Finding and removing Clever Hans: Using explanation methods to debug and improve deep models

The scientific work "Finding and removing Clever Hans: Using explanation methods to debug and improve deep models", with the support of iToBoS project, has been published.

Understanding DICOM

DICOM stands for Digital Imaging and COmmunications in Medicine: it is an international standard related to the exchange, storage and communication of digital medical images and other related digital data.

The value of clinical data

Over the last half century, clinicians and researchers have made enormous advances in detecting and treating melanoma.

Explain and improve: LRP-inference fine-tuning for image captioning models.

The scientific work "Explain and improve: LRP-inference fine-tuning for image captioning models.", with the support of iToBoS project, has been published.

Uncertainty Estimation in Deep Neural Networksfor Dermoscopic Image Classification

Machine learning and specifically deep learning, have dramatically improved the state-of-the-art in many areas of research, including computer vision, speech recognition, and natural language processing.

[GE] Hautkrebs: Forscher der Universität Hannover entwickeln neuen, intelligenten Ganzkörper-Scanner

In this document we present a video on the development of optics for the new generation of scanners of the iToBoS project. The document is in German.