Data-efficient knee anatomical landmark localization using deep learning

Abstract. Knee osteoarthritis (OA) is the most common musculoskeletal degenerative disease affecting the joints. OA is examined at a doctor’s visit and an X-ray image is often used to confirm the diagnosis. There is no treatment available for OA, therefore it is important to diagnose knee osteoarthritis at the earliest possible stage to preventpossible complications. Traditional methods used by a practitioners do not detect osteoarthritis as early as possible, therefore other methods are needed for early diagnosis. One possibility is to use novel quantitative imaging biomarkers, computation of which often requires precise understanding of the knee anatomy by a computer. More specifically, it is important to locate different areas of the knee according to anatomical atlases and place relevant regions of interest to compute the imaging biomarkers. A state-of-the-art approach for this problem is based on anatomical landmark localization. In this work, the localization of anatomical landmarks from knee X-rays using deep learning is investigated. To date, statistical methods have been used to localize landmarks, but this work focuses on identification based on deep learning and investigates how the amount of available training data affects performance. The method investigated in the present thesis is based on the KNEEL method developed earlier at the University of Oulu. The aim of this work was to improve this method by adjusting the training parameters and leveraging equivalent regularization for semi-supervised learning. Images from the Osteoarthritis Initiative database were used as material for training and validation. During the work, it was found that by adjusting the parameters used for training, anatomical landmarks can be localized more accurately than in the original KNEEL method. By adding the equivalent regularization, the accuracy of the localization was increased substantially, and a further enhancement in performance can be observed by utilizing unlabeled data in a semi-supervised learning manner. The results, developed in this thesis can layer be leveraged in OA research or even clinical practice, where the computation of quantitative imaging biomarkers is important. To our knowledge, this is the first work in OA where SSL and equivariant regularization were used.Datatehokas polven anatomisten maamerkkien paikantaminen käyttäen syväoppimista. Tiivistelmä. Polven nivelrikko on yleisin niveliin vaikuttava tuki- ja liikuntaelimistöä rappeuttava sairaus. Nivelrikko tutkitaan lääkärikäynnin yhteydessä ja diagnoosi vahvistetaan usein röntgenkuvantamisen avulla. Nivelrikkoon ei ole saatavilla hoitoa, joten on tärkeää diagnosoida polven nivelrikko mahdollisimman varhaisessa vaiheessa mahdollisten komplikaatioiden välttämiseksi. Perinteiset lääkäreiden käyttämät menetelmät eivät tunnista nivelrikkoa riittävän aikaisin, siksi tarvitaan muita menetelmiä varhaisempaan diagnostiikkaan. Yksi mahdollisuus on käyttää kvantitatiivisia kuvantamisbiomarkkereita, mutta näiden laskemiseksi tietokoneen täytyy ymmärtää anatomisia rakenteita tarkasti. Tarkemmin sanottuna on tärkeää paikantaa polven eri rakenteet ihmisen anatomiasta ja merkitä kiinnostavat rakenteet, jotta kuvantamisbiomarkkerit voidaan laskea. Nykyisin tätä ongelmaa lähestytään anatomisten maamerkkien paikantamisen avulla. Tässä työssä tutkittiin anatomisten maamerkkien paikantamista polven röntgenkuvista syväoppimisen avulla. Perinteisesti tähän on käytetty staattisia menetelmiä, mutta tässä työssä keskityttiin paikantamiseen käyttäen syväoppimista ja tutkittiin kuinka käytettävissä oleva opetusdatan määrä vaikuttaa suorituskykyyn. Työssä käytetty metodi perustuu aikaisemmin Oulun yliopistossa kehitettyyn KNEEL metodiin. Tämän työn tarkoituksena oli parantaa tätä metodia säätämällä opetusparametreja sekä hyödyntää ekvivalenttia regularisaatiota syväoppimisen yhteydessa. Kuvia The Osteoarthritis Initiative -tietokannasta käytettiin opetukseen ja validointiin. Työn aikana havaittiin, että säätämällä opetukseen käytettäviä parametrejä, voidaan anatomiset maamerkit paikantaa tarkemmin kuin alkuperäisellä KNEEL metodilla. Ekvivalentin regularisaation lisäämisellä paikantamisen tarkkuus lisääntyi huomattavasti. Suorituskyky parani entisestään käyttämällä annotoimatonta dataa puoli-ohjatun oppimisen yhteydessä. Tämän opinnäytetyön yhteydessä kehitettyä metodia voidaan käyttää nivelrikon tutkimuksen yhteydessä tai kliinisessä käytössä, missä kvantitatiivisten kuvantamisbiomarkkereiden käyttö on tärkeää. Tietojemme mukaan tämä työ on ensimmäinen, jossa käytetään puoliohjattua oppimista sekä ekvivalenttia regularisaatiota nivelrikon yhteydessä

Asymmetricity of ground-based GPS slant delay data

International audienceThe ground-based measurements of the Global Positioning System (GPS) allow estimation of the tropospheric delay along the slanted signal paths through the atmosphere. The meteorological exploitation of such slant delay (SD) observations relies on the hypothesis of azimuthal asymmetry of the information content. This article addresses the validity of the hypothesis. A new concept of asymmetricity is introduced for studying the SD observations and their model counterparts. The asymmetricity is defined as the ratio of the absolute asymmetric delay component to total SD. The model counterparts are determined from 3-h forecasts of a numerical weather prediction (NWP) model, run with four different horizontal resolutions. The SD observations are compared with their model counterparts with emphasis on cases of high asymmetricity in order to see whether the observed asymmetry is a real atmospheric signature. The asymmetricity is found to be of the order of a few parts per thousand. Thus, the asymmetric delay component barely exceeds the assumed standard deviation of the SD observation error. However, the observed asymmetric delay components show a statistically significant meteorological signal. Benefit of the asymmetric SD observations is therefore expected to be taken in future, when NWP systems will explicitly represent the small-scale atmospheric features revealed by the SD observations

Azimuthal asymmetry in ground-based GPS slant delay observations and their NWP model counterparts

International audienceThe ground-based measurements of the Global Positioning System (GPS) allow estimation of the tropospheric delay along the slanted signal paths through the atmosphere. The meteorological exploitation of such slant delay (SD) observations relies on the hypothesis of azimuthal asymmetry of the information content. This article addresses the validity of the hypothesis. The asymmetric properties of the SD observations and their model counterparts are investigated. In this study, the model counterparts are based on 3-h forecasts of a numerical weather prediction (NWP) model, run with four different horizontal resolutions. The SD observations are compared with their model counterparts with emphasis on cases of high asymmetry in order to see whether the observed asymmetry is a real atmospheric signature. The asymmetric delay component is found to be of the order of a few parts per thousand of the absolute SD value, thus barely exceeding the assumed standard deviation of the SD observation error. However, the observed asymmetric delay components show a statistically significant meteorological signal. Benefit of the asymmetric SD observations is therefore expected to be taken in future, when NWP systems will explicitly represent the small-scale atmospheric features revealed by the SD observations

Simple training tricks for mastering and taming bypass procedures in neurosurgery

Background: Neurosurgeons devoted to bypass neurosurgery or revascularization neurosurgery are becoming scarcer. From a practical point of view, 'bypass neurosurgeons' are anastomosis makers, vessels technicians, and time-racing repairers of vessel walls. This requires understanding the key features and hidden tricks of bypass surgery. The goal of this paper is to provide simple and inexpensive tricks for taming the art of bypass neurosurgery. Most of these tricks and materials described can be borrowed, donated, or purchased inexpensively. Methods: We performed a review of relevant training materials and recorded videos for training bypass procedures for 3 years between June 2014 and July 2017. In total, 1,300 training bypass procedures were performed, of which 200 procedures were chosen for this paper. Results : A training laboratory bypass procedures is required to enable a neurosurgeon to develop the necessary skills. The important skills for training bypass procedures gained through meticulous practice to be as reflexes are coordination, speed, agility, flexibility, and reaction time. Bypassing requires synchronization between the surgeon's gross movements, fine motoric skills, and mental strength. The suturing rhythm must be timed in a brain-body-hand fashion. Conclusion: Bypass-Training is a critical part of neurosurgical training and not for a selected few. Diligent and meticulous training can enable every neurosurgeon to tame the art of bypass neurosurgery. This requires understanding the key features and hidden tricks of bypass surgery, as well as uncountable hours of training. In bypass neurosurgery, quality and time goes hand in hand. © 2017 Surgical Neurology International | Published by Wolters Kluwer - Medknow.Peer reviewe

Sosiaaliturva ja elämänvaiheet : Suomen sosiaaliturvan kehitys esimerkkien ja tilastojen valossa

Sosiaaliturva ja elämänvaiheet kuvaa hyvinvointivaltiota sammakkoperspektiivistä. Kirja jäljittää kolmen nuoren esimerkkihenkilön – Ainon, Pertun ja Viivin – avulla sitä, kuinka paljon kukakin saa hyvinvointivaltiolta ja kuinka paljon maksaa sille eri elämänvaiheissa. Tarkastelu ulottuu jopa 70 vuoden päähän. Miten elämän mittaiseen sosiaaliturvaan vaikuttaa lumilautailuonnettomuus nuorena, pätkätyöt keski-iässä tai vanhuuden viimeiset vuodet vanhainkodissa? Kyseessä on helppolukuinen johdatus sosiaaliturvan historiaan, nykyiseen sosiaaliturvajärjestelmään ja sen rahoitukseen sekä tulevaisuuden näköaloihin. Kirja kertoo, miten suomalainen sosiaaliturva on elämässä mukana ja muutoksissa tukena. Kirjassa käsitellään paitsi tulonsiirtojen ja palveluiden myös kulutuksen ja verotuksen jakautumista eri elämänvaiheiden aikana. Viimeisessä luvussa otetaan kantaa ajankohtaiseen kysymykseen, riittävätkö rahat sosiaaliturvaan myös 70 vuoden kuluttua.10,00 euro

The environs of the H II region Gum 31

Aims. We analyze the distribution of the interstellar matter in the environs of the Hn region Gum 31, excited by the open cluster NGC 3324, located in the complex Carina region, with the aim of investigating the action of the massive stars on the surrounding neutral material. Methods. We use neutral hydrogen 21-cm line data, radio continuum images at 0.843, 2.4 and 4.9 GHz, 12CO(1-0) observations, and IRAS and MSX infrared data. Results. Adopting a distance of 3 kpc for the Hn region and the ionizing cluster, we derived an electron density of 33± 3 cm-3 and an ionized mass of (3.3 ±1.1) × 103 M⊙ based on the radio continuum data at 4.9 GHz. The Hl 21-cm line images revealed an Hl shell surrounding the Hn region. The Hl structure is 10.0 ±1.7 pc in radius, has a neutral mass of 1500 ±500 M⊙, and is expanding at 11 km s-1. The associated molecular gas amounts to (1.1 ±0.5) × 105 M⊙, being its volume density of about 350 cm-3. This molecular shell could represent the remains of the cloud where the young open cluster NGC 3324 was born or could have originated by the shock front associated with the Hn region. The difference between the ambient density and the electron density of the Hn region suggests that the Hn region is expanding. The distributions of the ionized and molecular material, along with that of the emission in the MSX band A, suggest that a photodissociation region has developed at the interface between the ionized and molecular gas. The copious UV photon flux from the early type stars in NGC 3324 keeps the Hn region ionized. The characteristics of a relatively large number of the IRAS, MSX, and 2MASS point sources projected onto the molecular envelope are compatible with protostellar candidates, showing the presence of active star forming regions. Very probably, the expansion of the Hn region has triggered stellar formation in the molecular shell.Instituto Argentino de RadioastronomíaInstituto de Astrofísica de La PlataFacultad de Ciencias Astronómicas y Geofísica

Ophiostoma spp. associated with pine- and spruce-infesting bark beetles in Finland and Russia

The timber and pulp industries of Finland rely heavily on importations from Russia as source of raw timber. These imports raise the risk of accidentally importing forest pests and pathogens, especially bark beetles and their associated fungi, into Finland. Although ophiostomatoid fungi have previously been reported from Finland and Russia, the risks of accidentally moving these fungi has prompted a first survey to compare the diversity of conifer-infesting bark beetles and associated fungi from boreal forests on both sides of the Finnish-Russian border. The aim of the present study was to identify and characterise Ophiostoma species isolated in association with 11 bark beetle species infesting Pinus sylvestris and Picea abies during this survey in the eastern parts of Finland and neighbouring Russia. Fungal isolates were grouped based on morphology and representatives of each morphological group were subjected to DNA sequence comparisons of the internal transcribed spaced region (ITS1, 5.8S, ITS2) and β-tubulin gene region. A total of 15 species of Ophiostoma were identified, including seven known species, five new species, and three species for which the identity remains uncertain. In the O. piceae-complex we identified O. canum, O. floccosum, O. karelicum and O. rachisporum sp. nov., and related to these, some isolates belonging to the European clade of O. minus in the O. minus-complex. Ophiostoma bicolor and O. fuscum sp. nov. were identified in the O. ips-complex, while O. ainoae, O. brunneo-ciliatum, O. tapionis sp. nov. and O. pallidulum sp. nov. were shown to group close to, but not in a strict monophyletic lineage with species of the O. ips-complex. Together with a single O. abietinum-like isolate, the only species that grouped close to the Sporothrix schenckii- O. stenoceras complex, was O. saponiodorum sp. nov

Hubble Space Telescope imaging of the WR 38/WR 38a cluster

We are conducting a high angular resolution imaging survey of Galactic Wolf-Rayet stars using the Wide Field Planetary Camera 2 aboard the Hubble Space Telescope (HST). We have found a small stellar cluster associated with the faint, close pair WR 38 and WR 38a. We present astrometric measurements and photometry in the wideband F336W (U), F439W (5), and F555W (V) filter system for the cluster and nearby stars. We combine our photometry with Johnson and IR magnitudes and compare the observations with calibrated model results for reddened stars to adjust the HST zero points and to identify five probable main-sequence members of the cluster. A least-squares fit of the colors and magnitudes of this set yields a cluster reddening of E(B - V) = 1.63 ±0.05 mag and a distance of 10 -4 +12 kpc for an assumed ratio of total to selective extinction of R = 3.1. We discuss the relationship of this cluster to other objects along the line of sight. If situated at a distance of ≈8 kpc, then the cluster would reside in a dense region of the Carina spiral arm, close to a giant molecular cloud and the starburst cluster NGC 3603.Facultad de Ciencias Astronómicas y Geofísica