Your browser doesn't support javascript.
loading
Deep Learning-Based Prediction Model for the Cobb Angle in Adolescent Idiopathic Scoliosis Patients.
Chui, Chun-Sing Elvis; He, Zhong; Lam, Tsz-Ping; Mak, Ka-Kwan Kyle; Ng, Hin-Ting Randy; Fung, Chun-Hai Ericsson; Chan, Mei-Shuen; Law, Sheung-Wai; Lee, Yuk-Wai Wayne; Hung, Lik-Hang Alec; Chu, Chiu-Wing Winnie; Mak, Sze-Yi Sibyl; Yau, Wing-Fung Edmond; Liu, Zhen; Li, Wu-Jun; Zhu, Zezhang; Wong, Man Yeung Ronald; Cheng, Chun-Yiu Jack; Qiu, Yong; Yung, Shu-Hang Patrick.
Afiliación
  • Chui CE; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • He Z; Division of Spine Surgery, Department of Orthopedic Surgery, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210000, China.
  • Lam TP; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Mak KK; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Ng HR; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Fung CE; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Chan MS; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Law SW; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Lee YW; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Hung LA; Department of Orthopaedics and Traumatology, Prince of Wales Hospital, Hong Kong, China.
  • Chu CW; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China.
  • Mak SS; Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
  • Yau WE; Koln 3D Technology (Medical) Limited Company, Hong Kong, China.
  • Liu Z; Division of Spine Surgery, Department of Orthopedic Surgery, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210000, China.
  • Li WJ; National Institute of Healthcare Data Science, Nanjing University, Nanjing 210023, China.
  • Zhu Z; National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China.
  • Wong MYR; Division of Spine Surgery, Department of Orthopedic Surgery, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210000, China.
  • Cheng CJ; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Qiu Y; Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, China.
  • Yung SP; Division of Spine Surgery, Department of Orthopedic Surgery, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210000, China.
Diagnostics (Basel) ; 14(12)2024 Jun 14.
Article en En | MEDLINE | ID: mdl-38928678
ABSTRACT
Scoliosis, characterized by spine deformity, is most common in adolescent idiopathic scoliosis (AIS). Manual Cobb angle measurement limitations underscore the need for automated tools. This study employed a vertebral landmark extraction method and Feedforward Neural Network (FNN) to predict scoliosis progression in 79 AIS patients. The novel intervertebral angles matrix format showcased results. The mean absolute error for the intervertebral angle progression was 1.5 degrees, while the Pearson correlation of the predicted Cobb angles was 0.86. The accuracy in classifying Cobb angles (<15°, 15-25°, 25-35°, 35-45°, >45°) was 0.85, with 0.65 sensitivity and 0.91 specificity. The FNN demonstrated superior accuracy, sensitivity, and specificity, aiding in tailored treatments for potential scoliosis progression. Addressing FNNs' over-fitting issue through strategies like "dropout" or regularization could further enhance their performance. This study presents a promising step towards automated scoliosis diagnosis and prognosis.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza