J 2024

Metrics reloaded: recommendations for image analysis validation

MAIER-HEIN, Lena, Annika REINKE, Patrick GODAU, Minu D TIZABI, Florian BUETTNER et. al.

Základní údaje

Originální název

Metrics reloaded: recommendations for image analysis validation

Autoři

MAIER-HEIN, Lena, Annika REINKE, Patrick GODAU, Minu D TIZABI, Florian BUETTNER, Evangelia CHRISTODOULOU, Ben GLOCKER, Fabian ISENSEE, Jens KLEESIEK, Michal KOZUBEK (203 Česká republika, garant, domácí), Mauricio REYES, Michael A RIEGLER, Manuel WIESENFARTH, A Emre KAVUR, Carole H SUDRE, Michael BAUMGARTNER, Matthias EISENMANN, Doreen HECKMANN-NOETZEL, Tim RAEDSCH, Laura ACION, Michela ANTONELLI, Tal ARBEL, Spyridon BAKAS, Arriel BENIS, Matthew B BLASCHKO, M Jorge CARDOSO, Veronika CHEPLYGINA, Beth A CIMINI, Gary S COLLINS, Keyvan FARAHANI, Luciana FERRER, Adrian GALDRAN, van Ginneken BRAM, Robert HAASE, Daniel A HASHIMOTO, Michael M HOFFMAN, Merel HUISMAN, Pierre JANNIN, Charles E KAHN, Dagmar KAINMUELLER, Bernhard KAINZ, Alexandros KARARGYRIS, Alan KARTHIKESALINGAM, Florian KOFLER, Annette KOPP-SCHNEIDER, Anna KRESHUK, Tahsin KURC, Bennett A LANDMAN, Geert LITJENS, Amin MADANI, Klaus MAIER-HEIN, Anne L MARTEL, Peter MATTSON, Erik MEIJERING, Bjoern MENZE, Karel G M MOONS, Henning MUELLER, Brennan NICHYPORUK, Felix NICKEL, Jens PETERSEN, Nasir RAJPOOT, Nicola RIEKE, Julio SAEZ-RODRIGUEZ, Clara I SANCHEZ, Shravya SHETTY, van Smeden MAARTEN, Ronald M SUMMERS, Abdel A TAHA, Aleksei TIULPIN, Sotirios A TSAFTARIS, Van Calster BEN, Gael VAROQUAUX a Paul F JAEGER

Vydání

NATURE METHODS, UNITED STATES, NATURE PORTFOLIO, 2024, 1548-7091

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 36.100 v roce 2023

Kód RIV

RIV/00216224:14330/24:00137721

Organizační jednotka

Fakulta informatiky

UT WoS

001161142200002

EID Scopus

2-s2.0-85184862654

Klíčová slova anglicky

HEALTH; SEGMENTATION; CRITERIA

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 4. 4. 2025 12:34, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint — a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Návaznosti

LM2018129, projekt VaV
Název: Národní infrastruktura pro biologické a medicínské zobrazování Czech-BioImaging
Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, National research infrastructure for biological and medical imaging

Přiložené soubory

MaierHein_NatMeth_2024.pdf
Požádat o autorskou verzi souboru