Literature DB >> 26162404

Diagnostic use of facial image analysis software in endocrine and genetic disorders: review, current results and future perspectives.

R P Kosilek1, R Frohner1, R P Würtz1, C M Berr1, J Schopohl1, M Reincke1, H J Schneider2.   

Abstract

Cushing's syndrome (CS) and acromegaly are endocrine diseases that are currently diagnosed with a delay of several years from disease onset. Novel diagnostic approaches and increased awareness among physicians are needed. Face classification technology has recently been introduced as a promising diagnostic tool for CS and acromegaly in pilot studies. It has also been used to classify various genetic syndromes using regular facial photographs. The authors provide a basic explanation of the technology, review available literature regarding its use in a medical setting, and discuss possible future developments. The method the authors have employed in previous studies uses standardized frontal and profile facial photographs for classification. Image analysis is based on applying mathematical functions evaluating geometry and image texture to a grid of nodes semi-automatically placed on relevant facial structures, yielding a binary classification result. Ongoing research focuses on improving diagnostic algorithms of this method and bringing it closer to clinical use. Regarding future perspectives, the authors propose an online interface that facilitates submission of patient data for analysis and retrieval of results as a possible model for clinical application.
© 2015 European Society of Endocrinology.

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Mesh:

Year:  2015        PMID: 26162404     DOI: 10.1530/EJE-15-0429

Source DB:  PubMed          Journal:  Eur J Endocrinol        ISSN: 0804-4643            Impact factor:   6.664


  8 in total

Review 1.  The risks of overlooking the diagnosis of secreting pituitary adenomas.

Authors:  Thierry Brue; Frederic Castinetti
Journal:  Orphanet J Rare Dis       Date:  2016-10-06       Impact factor: 4.123

Review 2.  Towards an Earlier Diagnosis of Acromegaly and Gigantism.

Authors:  Jill Sisco; A J van der Lely
Journal:  J Clin Med       Date:  2021-03-26       Impact factor: 4.241

Review 3.  Machine intelligence in non-invasive endocrine cancer diagnostics.

Authors:  Nicole M Thomasian; Ihab R Kamel; Harrison X Bai
Journal:  Nat Rev Endocrinol       Date:  2021-11-09       Impact factor: 43.330

4.  A New Clinical Model to Estimate the Pre-Test Probability of Cushing's Syndrome: The Cushing Score.

Authors:  Mirko Parasiliti-Caprino; Fabio Bioletto; Tommaso Frigerio; Valentina D'Angelo; Filippo Ceccato; Francesco Ferraù; Rosario Ferrigno; Marianna Minnetti; Carla Scaroni; Salvatore Cannavò; Rosario Pivonello; Andrea Isidori; Fabio Broglio; Roberta Giordano; Maurizio Spinello; Silvia Grottoli; Emanuela Arvat
Journal:  Front Endocrinol (Lausanne)       Date:  2021-10-05       Impact factor: 5.555

Review 5.  Review on Facial-Recognition-Based Applications in Disease Diagnosis.

Authors:  Jiaqi Qiang; Danning Wu; Hanze Du; Huijuan Zhu; Shi Chen; Hui Pan
Journal:  Bioengineering (Basel)       Date:  2022-06-23

6.  Identifying Facial Features and Predicting Patients of Acromegaly Using Three-Dimensional Imaging Techniques and Machine Learning.

Authors:  Tian Meng; Xiaopeng Guo; Wei Lian; Kan Deng; Lu Gao; Zihao Wang; Jiuzuo Huang; Xiaojun Wang; Xiao Long; Bing Xing
Journal:  Front Endocrinol (Lausanne)       Date:  2020-07-29       Impact factor: 5.555

Review 7.  Toward a Diagnostic Score in Cushing's Syndrome.

Authors:  Leah T Braun; Anna Riester; Andrea Oßwald-Kopp; Julia Fazel; German Rubinstein; Martin Bidlingmaier; Felix Beuschlein; Martin Reincke
Journal:  Front Endocrinol (Lausanne)       Date:  2019-11-08       Impact factor: 5.555

8.  [Selective screening of patients with associated somatic diseases as a method of early detection of acromegaly].

Authors:  M B Antsiferov; V S Pronin; T M Alekseeva; O A Ionova; E Y Martynova; Yu E Poteshkin; N A Chubrova; K Y Zherebchikova
Journal:  Probl Endokrinol (Mosk)       Date:  2021-01-08
  8 in total

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